{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,18]],"date-time":"2026-01-18T11:49:22Z","timestamp":1768736962898,"version":"3.49.0"},"reference-count":295,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,2,13]],"date-time":"2025-02-13T00:00:00Z","timestamp":1739404800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,2,13]],"date-time":"2025-02-13T00:00:00Z","timestamp":1739404800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Spanish Government","award":["TIN2017-89156-R"],"award-info":[{"award-number":["TIN2017-89156-R"]}]},{"name":"Spanish Government","award":["PID2020-113416RB-I00"],"award-info":[{"award-number":["PID2020-113416RB-I00"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Auton Agent Multi-Agent Syst"],"published-print":{"date-parts":[[2025,6]]},"DOI":"10.1007\/s10458-025-09692-x","type":"journal-article","created":{"date-parts":[[2025,2,13]],"date-time":"2025-02-13T08:23:31Z","timestamp":1739435011000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["An introduction to computational argumentation research from a human argumentation perspective"],"prefix":"10.1007","volume":"39","author":[{"given":"Ramon","family":"Ruiz-Dolz","sequence":"first","affiliation":[]},{"given":"Stella","family":"Heras","sequence":"additional","affiliation":[]},{"given":"Ana","family":"Garc\u00eda-Fornes","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,2,13]]},"reference":[{"key":"9692_CR1","doi-asserted-by":"publisher","unstructured":"Addawood, A., & Bashir, M.N. (2016). \u201cWhat is your evidence?\u201d A study of controversial topics on social media. In Proceedings of the 3rd workshop on argument mining, ArgMining@ACL. The Association for Computer Linguistics. https:\/\/doi.org\/10.18653\/v1\/w16-2801","DOI":"10.18653\/v1\/w16-2801"},{"key":"9692_CR2","doi-asserted-by":"publisher","unstructured":"Ajjour, Y., Chen, W.F., Kiesel, J., Wachsmuth, H., & Stein, B. (2017). Unit segmentation of argumentative texts. In Proceedings of the 4th workshop on argument mining, ArgMining@EMNLP. Association for Computational Linguistics, (pp. 118\u2013128). https:\/\/doi.org\/10.18653\/v1\/w17-5115","DOI":"10.18653\/v1\/w17-5115"},{"key":"9692_CR3","doi-asserted-by":"publisher","unstructured":"Aker, A., Sliwa, A., Ma, Y., Lui, R., Borad, N., Ziyaei, S., & Ghobadi, M. (2017). What works and what does not: Classifier and feature analysis for argument mining. In Proceedings of the 4th workshop on argument mining, ArgMining@EMNLP. Association for Computational Linguistics, (pp. 91\u201396). https:\/\/doi.org\/10.18653\/v1\/w17-5112","DOI":"10.18653\/v1\/w17-5112"},{"key":"9692_CR4","doi-asserted-by":"crossref","unstructured":"Al-Khatib, K., Hou, Y., Wachsmuth, H., Jochim, C., Bonin, F., & Stein, B. (2020). End-to-end argumentation knowledge graph construction. In Proceedings of the AAAI conference on artificial intelligence (pp. 7367\u20137374).","DOI":"10.1609\/aaai.v34i05.6231"},{"key":"9692_CR5","unstructured":"Alahmari, S., Yuan, T., & Kudenko, D. (2019a). Reinforcement learning for dialogue game based argumentation. In Proceedings of the 19th Workshop on Computational Models of Natural Argument, CMNA@PERSUASIVE CEUR-WS.org (vol 2346, pp. 29\u201337). http:\/\/ceur-ws.org\/Vol-2346\/paper3.pdf"},{"key":"9692_CR6","unstructured":"Alahmari, S., Yuan, T., & Kudenko, D. (2019b). Reinforcement learning of dialogue coherence and relevance. In Proceedings of the 19th workshop on computational models of natural argument (vol. 2346, pp. 38\u201348). CMNA@PERSUASIVE, CEUR-WS.org.http:\/\/ceur-ws.org\/Vol-2346\/paper4.pdf"},{"key":"9692_CR7","doi-asserted-by":"publisher","unstructured":"Alfano, G., Greco, S., & Parisi, F. (2017). Efficient computation of extensions for dynamic abstract argumentation frameworks: An incremental approach. In Proceedings of the 26th international joint conference on artificial intelligence (pp. 49\u201355). IJCAI. ijcai.org. https:\/\/doi.org\/10.24963\/ijcai.2017\/8","DOI":"10.24963\/ijcai.2017\/8"},{"key":"9692_CR8","doi-asserted-by":"publisher","unstructured":"Alhamzeh, A., Bouhaouel, M., Egyed-Zsigmond, E., Mitrovi\u0107, J., Brunie, L., & Kosch, H. (2021). A stacking approach for cross-domain argument identification. In Database and expert systems applications - 32nd international conference. Proceedings, Part I, Lecture Notes in Computer Science, DEXA 2021, Virtual Event, September 27-30, 2021. (vol. 12923, pp. 361\u2013373). Springer. https:\/\/doi.org\/10.1007\/978-3-030-86472-9_33","DOI":"10.1007\/978-3-030-86472-9_33"},{"key":"9692_CR9","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1007\/978-3-662-66146-8_5","volume":"52","author":"A Alhamzeh","year":"2022","unstructured":"Alhamzeh, A., Egyed-Zsigmond, E., Mekki, D.E., Khayari, A.E., Mitrovi\u0107, J., Brunie, L., & Kosch, H.\u00a0(2022). Empirical study of the model generalization for argument mining in cross-domain and cross-topic settings. Transactions on Large-Scale Data-and Knowledge-Centered Systems, 52, 103\u2013126. https:\/\/doi.org\/10.1007\/978-3-662-66146-8_5","journal-title":"Transactions on Large-Scale Data-and Knowledge-Centered Systems"},{"key":"9692_CR10","doi-asserted-by":"publisher","unstructured":"Amgoud, L., & Ben-Naim, J. (2013). Ranking-based semantics for argumentation frameworks. In Scalable uncertainty management - 7th international conference, SUM (vol. 8078, pp. 134\u2013147). Springer. https:\/\/doi.org\/10.1007\/978-3-642-40381-1_11","DOI":"10.1007\/978-3-642-40381-1_11"},{"key":"9692_CR11","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1016\/j.ijar.2018.05.004","volume":"99","author":"L Amgoud","year":"2018","unstructured":"Amgoud, L., & Ben-Naim, J. (2018). Evaluation of arguments in weighted bipolar graphs. International Journal of Approximate Reasoning, 99, 39\u201355. https:\/\/doi.org\/10.1016\/j.ijar.2018.05.004","journal-title":"International Journal of Approximate Reasoning"},{"key":"9692_CR12","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1023\/A:1021603608656","volume":"29","author":"L Amgoud","year":"2002","unstructured":"Amgoud, L., & Cayrol, C. (2002). Inferring from inconsistency in preference-based argumentation frameworks. Journal of Automated Reasoning, 29, 125\u2013169.","journal-title":"Journal of Automated Reasoning"},{"issue":"2","key":"9692_CR13","doi-asserted-by":"publisher","first-page":"149","DOI":"10.1007\/s10472-011-9271-9","volume":"63","author":"L Amgoud","year":"2011","unstructured":"Amgoud, L., & Vesic, S. (2011). A new approach for preference-based argumentation frameworks. Annals of Mathematics and Artificial Intelligence, 63(2), 149\u2013183. https:\/\/doi.org\/10.1007\/s10472-011-9271-9","journal-title":"Annals of Mathematics and Artificial Intelligence"},{"issue":"2","key":"9692_CR14","doi-asserted-by":"publisher","first-page":"585","DOI":"10.1016\/j.ijar.2013.10.010","volume":"55","author":"L Amgoud","year":"2014","unstructured":"Amgoud, L., & Vesic, S. (2014). Rich preference-based argumentation frameworks. International Journal of Approximate Reasoning, 55(2), 585\u2013606. https:\/\/doi.org\/10.1016\/j.ijar.2013.10.010","journal-title":"International Journal of Approximate Reasoning"},{"key":"9692_CR15","doi-asserted-by":"crossref","unstructured":"Amgoud, L., Maudet, N., & Parsons, S. (2000). Modelling dialogues using argumentation. In Proceedings 4th international conference on multiagent systems (pp. 31\u201338)\/. IEEE.","DOI":"10.1109\/ICMAS.2000.858428"},{"issue":"10","key":"9692_CR16","doi-asserted-by":"publisher","first-page":"1062","DOI":"10.1002\/int.20307","volume":"23","author":"L Amgoud","year":"2008","unstructured":"Amgoud, L., Cayrol, C., Lagasquie\u2013Schiex, M. C., & Livet, P.\u00a0(2008). On bipolarity in argumentation frameworks. International Journal of Intelligent Systems, 23(10), 1062\u20131093. https:\/\/doi.org\/10.1002\/int.20307","journal-title":"International Journal of Intelligent Systems"},{"issue":"23","key":"9692_CR17","doi-asserted-by":"publisher","first-page":"713","DOI":"10.2307\/2023169","volume":"58","author":"AR Anderson","year":"1961","unstructured":"Anderson, A. R., & Belnap, N. D. (1961). Enthymemes. The Journal of Philosophy, 58(23), 713\u2013723.","journal-title":"The Journal of Philosophy"},{"key":"9692_CR18","volume-title":"Aristotle\u2019s Politics","author":"Aristotle","year":"1905","unstructured":"Aristotle. (1905). Aristotle\u2019s Politics. Clarendon Press."},{"issue":"3","key":"9692_CR19","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1609\/aimag.v38i3.2704","volume":"38","author":"K Atkinson","year":"2017","unstructured":"Atkinson, K., Baroni, P., Giacomin, M., Hunter, A., Prakken, H., Reed, C., Simari, G., Thimm, M., & Villata, S.\u00a0(2017). Towards artificial argumentation. AI Magazine, 38(3), 25\u201336. https:\/\/doi.org\/10.1609\/aimag.v38i3.2704","journal-title":"AI Magazine"},{"key":"9692_CR20","doi-asserted-by":"crossref","unstructured":"El Baff, R., Wachsmuth, H., Al Khatib, K., Stede, M., & Stein, B. (2019). Computational argumentation synthesis as a language modeling task. In Proceedings of the 12th international conference on natural language generation (pp. 54\u201364). INLG. Association for Computational Linguistics. https:\/\/aclanthology.org\/W19-8607\/","DOI":"10.18653\/v1\/W19-8607"},{"key":"9692_CR21","doi-asserted-by":"publisher","unstructured":"El Baff, R., Wachsmuth, H., Al Khatib, K., & Stein, B. (2020). Analyzing the persuasive effect of style in news editorial argumentation. In Proceedings of the 58th annual meeting of the association for computational linguistics) ACL. Association for Computational Linguistics. (pp. 3154\u20133160). https:\/\/doi.org\/10.18653\/v1\/2020.acl-main.287","DOI":"10.18653\/v1\/2020.acl-main.287"},{"key":"9692_CR22","doi-asserted-by":"publisher","unstructured":"Bao, J., Fan, C., Wu, J., Dang, Y., Du, J., & Xu, R. (2021). A neural transition-based model for argumentation mining. In Proceedings of the 59th annual meeting of the association for computational linguistics and the 11th international joint conference on natural language processing ACL\/IJCNLP 2021, (Volume 1: Long Papers), Virtual Event, August 1-6, 2021. (pp. 6354\u20136364). Association for Computational Linguistics. https:\/\/doi.org\/10.18653\/v1\/2021.acl-long.497","DOI":"10.18653\/v1\/2021.acl-long.497"},{"key":"9692_CR23","doi-asserted-by":"crossref","unstructured":"Bao, J., He, Y., Sun, Y., Liang, B., Du, J., Qin, B., Yang, M., & Xu, R. (2022). A generative model for end-to-end argument mining with reconstructed positional encoding and constrained pointer mechanism. In Proceedings of the 2022 conference on empirical methods in natural language processing EMNLP 2022, Abu Dhabi, United Arab Emirates, December 7-11, 2022 (pp. 10437\u201310449). Association for Computational Linguistics. https:\/\/aclanthology.org\/2022.emnlp-main.713","DOI":"10.18653\/v1\/2022.emnlp-main.713"},{"key":"9692_CR24","doi-asserted-by":"publisher","unstructured":"Bar-Haim, R., Krieger, D., Toledo-Ronen, O., Edelstein, L., Bilu, Y., Halfon, A., Katz, Y., Menczel, A., Aharonov, R., & Slonim, N. (2019). From surrogacy to adoption; from bitcoin to cryptocurrency: Debate topic expansion. In Proceedings of the 57th conference of the association for computational linguistics (pp. 977\u2013990). ACL. Association for Computational Linguistics. https:\/\/doi.org\/10.18653\/v1\/p19-1094","DOI":"10.18653\/v1\/p19-1094"},{"key":"9692_CR25","doi-asserted-by":"publisher","unstructured":"Baroni, P., & Giacomin, M. (2009). Semantics of abstract argument systems. In Argumentation in artificial intelligence (pp. 25\u201344). Springer. https:\/\/doi.org\/10.1007\/978-0-387-98197-0_2","DOI":"10.1007\/978-0-387-98197-0_2"},{"issue":"1\u20132","key":"9692_CR26","doi-asserted-by":"publisher","first-page":"162","DOI":"10.1016\/j.artint.2005.05.006","volume":"168","author":"P Baroni","year":"2005","unstructured":"Baroni, P., Giacomin, M., & Guida, G. (2005). Scc-recursiveness: A general schema for argumentation semantics. Artificial Intelligence, 168(1\u20132), 162\u2013210. https:\/\/doi.org\/10.1016\/j.artint.2005.05.006","journal-title":"Artificial Intelligence"},{"issue":"4","key":"9692_CR27","doi-asserted-by":"publisher","first-page":"365","DOI":"10.1017\/S0269888911000166","volume":"26","author":"P Baroni","year":"2011","unstructured":"Baroni, P., Caminada, M., & Giacomin, M. (2011). An introduction to argumentation semantics. The Knowledge Engineering Review, 26(4), 365\u2013410. https:\/\/doi.org\/10.1017\/S0269888911000166","journal-title":"The Knowledge Engineering Review"},{"key":"9692_CR28","doi-asserted-by":"publisher","first-page":"104","DOI":"10.1016\/j.artint.2014.03.003","volume":"212","author":"P Baroni","year":"2014","unstructured":"Baroni, P., Giacomin, M., & Liao, B. (2014). On topology-related properties of abstract argumentation semantics. A correction and extension to dynamics of argumentation systems: A division-based method. Artificial Intelligence, 212, 104\u2013115. https:\/\/doi.org\/10.1016\/j.artint.2014.03.003","journal-title":"Artificial Intelligence"},{"issue":"1","key":"9692_CR29","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1080\/19462166.2014.1001791","volume":"6","author":"P Baroni","year":"2015","unstructured":"Baroni, P., Romano, M., Toni, F., Aurisicchio, M., & Bertanza, G.\u00a0(2015). Automatic evaluation of design alternatives with quantitative argumentation. Argument & Computation, 6(1), 24\u201349. https:\/\/doi.org\/10.1080\/19462166.2014.1001791","journal-title":"Argument & Computation"},{"key":"9692_CR30","volume-title":"Handbook of formal argumentation","author":"P Baroni","year":"2018","unstructured":"Baroni, P., Gabbay, D., Giacomin, M, & Van der Torre, L.\u00a0(2018). Handbook of formal argumentation. College Publications."},{"key":"9692_CR31","doi-asserted-by":"crossref","unstructured":"Baroni, P., Rago, A., & Toni, F. (2018b). How many properties do we need for gradual argumentation? In Proceedings of the 32nd AAAI conference on artificial intelligence, (AAAI-18). (pp. 1736\u20131743). AAAI Press. https:\/\/www.aaai.org\/ocs\/index.php\/AAAI\/AAAI18\/paper\/view\/16280","DOI":"10.1609\/aaai.v32i1.11544"},{"issue":"4","key":"9692_CR32","doi-asserted-by":"publisher","first-page":"427","DOI":"10.58680\/ccc198015935","volume":"31","author":"P Bator","year":"1980","unstructured":"Bator, P. (1980). Aristotelian and rogerian rhetoric. College Composition and Communication, 31(4), 427\u2013432.","journal-title":"College Composition and Communication"},{"key":"9692_CR33","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.artint.2018.08.001","volume":"264","author":"D Baumeister","year":"2018","unstructured":"Baumeister, D., Neugebauer, D., Rothe, J., & Schadrack, H.\u00a0(2018). Verification in incomplete argumentation frameworks. Artificial Intelligence, 264, 1\u201326. https:\/\/doi.org\/10.1016\/j.artint.2018.08.001","journal-title":"Artificial Intelligence"},{"key":"9692_CR34","unstructured":"Bench-Capon, T.J.M. (2002). Value-based argumentation frameworks. In 9th international workshop on non-monotonic reasoning (NMR). (pp. 443\u2013454)."},{"issue":"10\u201315","key":"9692_CR35","doi-asserted-by":"publisher","first-page":"619","DOI":"10.1016\/j.artint.2007.05.001","volume":"171","author":"TJM Bench-Capon","year":"2007","unstructured":"Bench-Capon, T. J. M., & Dunne, P. E. (2007). Argumentation in artificial intelligence. Artificial Intelligence, 171(10\u201315), 619\u2013641. https:\/\/doi.org\/10.1016\/j.artint.2007.05.001","journal-title":"Artificial Intelligence"},{"issue":"1\u20132","key":"9692_CR36","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1016\/S0004-3702(01)00071-6","volume":"128","author":"P Besnard","year":"2001","unstructured":"Besnard, P., & Hunter, A. (2001). A logic-based theory of deductive arguments. Artificial Intelligence, 128(1\u20132), 203\u2013235. https:\/\/doi.org\/10.1016\/S0004-3702(01)00071-6","journal-title":"Artificial Intelligence"},{"key":"9692_CR37","doi-asserted-by":"publisher","unstructured":"Besnard, P., & Hunter, A. (2009). Argumentation based on classical logic. In Argumentation in artificial intelligence (pp. 133\u2013152). Springer. https:\/\/doi.org\/10.1007\/978-0-387-98197-0_7","DOI":"10.1007\/978-0-387-98197-0_7"},{"issue":"5","key":"9692_CR38","doi-asserted-by":"publisher","first-page":"951","DOI":"10.1093\/logcom\/exs033","volume":"23","author":"F Bex","year":"2013","unstructured":"Bex, F., Modgil, S., Prakken, H., & Reed, C.\u00a0(2013). On logical specifications of the argument interchange format. Journal of Logic and Computation, 23(5), 951\u2013989.","journal-title":"Journal of Logic and Computation"},{"key":"9692_CR39","doi-asserted-by":"crossref","unstructured":"Bhattacharya, P., Paul, S., Ghosh, K., Ghosh, S., & Wyner, A. (2019). Identification of rhetorical roles of sentences in Indian legal judgments. In legal knowledge and information systems (pp. 3\u201312). IOS Press.","DOI":"10.3233\/FAIA190301"},{"key":"9692_CR40","doi-asserted-by":"publisher","unstructured":"Bilu, Y., & Slonim, N. (2016). Claim synthesis via predicate recycling. In Proceedings of the 54th annual meeting of the association for computational linguistics ACL. The Association for Computer Linguistics. https:\/\/doi.org\/10.18653\/v1\/p16-2085","DOI":"10.18653\/v1\/p16-2085"},{"key":"9692_CR41","doi-asserted-by":"publisher","unstructured":"Bilu, Y., Gera, A., Hershcovich, D., Sznajder, B., Lahav, D., Moshkowich, G., Malet, A., Gavron, A., & Slonim, N. (2019). Argument invention from first principles. In Proceedings of the 57th conference of the association for computational linguistics (pp. 1013\u20131026). ACL. Association for Computational Linguistics. https:\/\/doi.org\/10.18653\/v1\/p19-1097","DOI":"10.18653\/v1\/p19-1097"},{"key":"9692_CR42","doi-asserted-by":"publisher","unstructured":"Bisquert, P., Cayrol, C., de Saint-Cyr, F.D, & Lagasquie-Schiex, M.C. (2011). Change in argumentation systems: Exploring the interest of removing an argument. In Scalable uncertainty management - 5th international conference SUM (vol. 6929, pp 275\u2013288). Springer. https:\/\/doi.org\/10.1007\/978-3-642-23963-2_22","DOI":"10.1007\/978-3-642-23963-2_22"},{"key":"9692_CR43","doi-asserted-by":"publisher","unstructured":"Bistarelli, S., & Santini, F. (2019). Well-foundedness in weighted argumentation frameworks. In Logics in artificial intelligence - 16th European conference JELIA (vol. 11468 pp 69\u201384). Springer. https:\/\/doi.org\/10.1007\/978-3-030-19570-0_5","DOI":"10.1007\/978-3-030-19570-0_5"},{"key":"9692_CR44","doi-asserted-by":"crossref","unstructured":"Black, E., & Hunter, A. (2008). Using enthymemes in an inquiry dialogue system. In Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems-Volume 1 Citeseer. (pp. 437\u2013444).","DOI":"10.1145\/1329125.1329417"},{"issue":"1","key":"9692_CR45","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1093\/logcom\/exp064","volume":"22","author":"E Black","year":"2012","unstructured":"Black, E., & Hunter, A. (2012). A relevance-theoretic framework for constructing and deconstructing enthymemes. Journal of Logic and Computation, 22(1), 55\u201378.","journal-title":"Journal of Logic and Computation"},{"key":"9692_CR46","doi-asserted-by":"publisher","unstructured":"Boella, G., Kaci, S., & van\u00a0der Torre, L.W.N. (2009a). Dynamics in argumentation with single extensions: Abstraction principles and the grounded extension. In Symbolic and quantitative approaches to reasoning with uncertainty, 10th European conference ECSQARU (vol. 5590, pp. 107\u2013118). Springer. https:\/\/doi.org\/10.1007\/978-3-642-02906-6_11","DOI":"10.1007\/978-3-642-02906-6_11"},{"key":"9692_CR47","doi-asserted-by":"publisher","unstructured":"Boella, G., Kaci, S., & van\u00a0der Torre, L.W.N. (2009b). Dynamics in argumentation with single extensions: Attack refinement and the grounded extension (extended version). In Argumentation in multi-agent systems, 6th international workshop, ArgMAS (vol. 6057, pp. 150\u2013159). Springer. https:\/\/doi.org\/10.1007\/978-3-642-12805-9_9","DOI":"10.1007\/978-3-642-12805-9_9"},{"key":"9692_CR48","doi-asserted-by":"publisher","unstructured":"Boltuzic, F., & Snajder, J. (2014). Back up your stance: Recognizing arguments in online discussions. In Proceedings of the first workshop on argument mining ArgMining@ACL (pp. 49\u201358). The Association for Computer Linguistics. https:\/\/doi.org\/10.3115\/v1\/w14-2107.","DOI":"10.3115\/v1\/w14-2107"},{"key":"9692_CR49","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1016\/S0004-3702(97)00015-5","volume":"93","author":"A Bondarenko","year":"1997","unstructured":"Bondarenko, A., Dung, P.M., Kowalski, R.A., & Toni, F.\u00a0(1997). An abstract, argumentation-theoretic approach to default reasoning. Artificial Intelligence, 93, 63\u2013101. https:\/\/doi.org\/10.1016\/S0004-3702(97)00015-5","journal-title":"Artificial Intelligence"},{"key":"9692_CR50","doi-asserted-by":"crossref","unstructured":"Bondarenko, A., Fr\u00f6be, M., Kiesel, J., Syed, S., Gurcke, T., Beloucif, M., Panchenko, A., Biemann, C., Stein, B., Wachsmuth, H., & Potthast, M. (2022). Overview of touch\u00e9 2022: Argument retrieval. In International conference of the cross-language evaluation forum for European languages (pp. 311\u2013336). Springer.","DOI":"10.1007\/978-3-031-13643-6_21"},{"key":"9692_CR51","doi-asserted-by":"crossref","unstructured":"Bosselut, A., Rashkin, H., Sap, M., Malaviya, C., Celikyilmaz, A., & Choi, Y. (2019). Comet: Commonsense transformers for automatic knowledge graph construction. InProceedings of the 57th annual meeting of the association for computational linguistics (pp. 4762\u20134779).","DOI":"10.18653\/v1\/P19-1470"},{"key":"9692_CR52","doi-asserted-by":"publisher","unstructured":"Bouslama, R., Ayachi, R., & Amor, N.B. (2019). Using convolutional neural network in cross-domain argumentation mining framework. In Scalable uncertainty management - 13th international conference, Proceedings, Lecture Notes in Computer Science SUM 2019 Compi\u00e8gne, France, December 16-18, 2019 (vol. 11940, pp 355\u2013367) Springer. https:\/\/doi.org\/10.1007\/978-3-030-35514-2_26","DOI":"10.1007\/978-3-030-35514-2_26"},{"key":"9692_CR53","unstructured":"Brewka, G., & Woltran, S. (2010). Abstract dialectical frameworks. In Principles of knowledge representation and reasoning: Proceedings of the 12th international conference KR. AAAI Press. http:\/\/aaai.org\/ocs\/index.php\/KR\/KR2010\/paper\/view\/1294"},{"key":"9692_CR54","doi-asserted-by":"crossref","unstructured":"Brewka, G., Strass, H., Wallner, J., & Woltran, S. (2018). Weighted abstract dialectical frameworks. In Proceedings of the AAAI conference on artificial intelligence.","DOI":"10.1609\/aaai.v32i1.11545"},{"key":"9692_CR55","unstructured":"Budzynska, K., Janier, M., Reed, C., Saint-Dizier, P., Stede, M., & Yaskorska, O. (2014). A model for processing illocutionary structures and argumentation in debates. In Proceedings of the 9th international conference on language resources and evaluation, LREC 2014, Reykjavik, Iceland, May 26-31, 2014. (pp. 917\u2013924). European Language Resources Association (ELRA). http:\/\/www.lrec-conf.org\/proceedings\/lrec2014\/summaries\/77.html"},{"key":"9692_CR56","unstructured":"Cabrio, E., & Villata, S. (2012). Combining textual entailment and argumentation theory for supporting online debates interactions. In The 50th annual meeting of the association for computational linguistics. (pp. 208\u2013212). The Association for Computer Linguistics. https:\/\/aclanthology.org\/P12-2041\/."},{"key":"9692_CR57","doi-asserted-by":"publisher","unstructured":"Cabrio, E., & Villata, S. (2018). Five years of argument mining: A data-driven analysis. In Proceedings of the 27th international joint conference on artificial intelligence (pp. 5427\u20135433). IJCAI. ijcai.org. https:\/\/doi.org\/10.24963\/ijcai.2018\/766","DOI":"10.24963\/ijcai.2018\/766"},{"key":"9692_CR58","unstructured":"Caminada, M. (2006). Semi-stable semantics. In Computational models of argument: Proceedings of COMMA (vol. 144. pp. 121\u2013130). IOS Press. http:\/\/www.booksonline.iospress.nl\/Content\/View.aspx?piid=1932"},{"issue":"5\u20136","key":"9692_CR59","doi-asserted-by":"publisher","first-page":"286","DOI":"10.1016\/j.artint.2007.02.003","volume":"171","author":"M Caminada","year":"2007","unstructured":"Caminada, M., & Amgoud, L. (2007). On the evaluation of argumentation formalisms. Artificial Intelligence, 171(5\u20136), 286\u2013310.","journal-title":"Artificial Intelligence"},{"issue":"5","key":"9692_CR60","doi-asserted-by":"publisher","first-page":"1207","DOI":"10.1093\/logcom\/exr033","volume":"22","author":"MW Caminada","year":"2012","unstructured":"Caminada, M. W., Carnielli, W. A., & Dunne, P. E. (2012). Semi-stable semantics. Journal of Logic and Computation, 22(5), 1207\u20131254.","journal-title":"Journal of Logic and Computation"},{"issue":"11","key":"9692_CR61","doi-asserted-by":"publisher","first-page":"925","DOI":"10.1016\/j.artint.2006.05.003","volume":"170","author":"G Carenini","year":"2006","unstructured":"Carenini, G., & Moore, J. D. (2006). Generating and evaluating evaluative arguments. Artificial Intelligence, 170(11), 925\u2013952. https:\/\/doi.org\/10.1016\/j.artint.2006.05.003","journal-title":"Artificial Intelligence"},{"key":"9692_CR62","doi-asserted-by":"publisher","unstructured":"Carstens, L., & Toni, F. (2015). Towards relation based argumentation mining. In Proceedings of the 2nd Workshop on Argumentation Mining ArgMining@HLT-NAACL (pp. 29\u201334). The Association for Computational Linguistics. https:\/\/doi.org\/10.3115\/v1\/w15-0504","DOI":"10.3115\/v1\/w15-0504"},{"key":"9692_CR63","doi-asserted-by":"publisher","unstructured":"Cayrol, C., & Lagasquie-Schiex, M. (2005). On the acceptability of arguments in bipolar argumentation frameworks. In Symbolic and quantitative approaches to reasoning with uncertainty, 8th European conference , ECSQARU (vol. 3571, pp. 378\u2013389). Springer. https:\/\/doi.org\/10.1007\/11518655_33","DOI":"10.1007\/11518655_33"},{"key":"9692_CR64","unstructured":"Cayrol, C., de\u00a0Saint-Cyr, F.D., & Lagasquie-Schiex, M. (2014). Change in abstract argumentation frameworks: Adding an argument. CoRR abs\/1401.3838. http:\/\/arxiv.org\/abs\/1401.3838"},{"key":"9692_CR65","doi-asserted-by":"publisher","unstructured":"Cerutti, F., Tintarev, N., & Oren, N. (2014). Formal arguments, preferences, and natural language interfaces to humans: An empirical evaluation. In ECAI 2014 - 21st European conference on artificial intelligence (vol. 263, pp. 207\u2013212). IOS Press. https:\/\/doi.org\/10.3233\/978-1-61499-419-0-207","DOI":"10.3233\/978-1-61499-419-0-207"},{"key":"9692_CR66","unstructured":"Cerutti, F., Gaggl, S.A., Thimm, M., & Wallner, J. (2017). Foundations of implementations for formal argumentation. FLAP 4(8). http:\/\/www.collegepublications.co.uk\/downloads\/ifcolog00017.pdf"},{"key":"9692_CR67","unstructured":"Cerutti, F., Cramer, M., Guillaume, M., Hadoux, E., Hunter, A., & Polberg, S. (2021). Empirical cognitive studies about formal argumentation. Handbook of Formal Argumentation (vol. 2)."},{"key":"9692_CR68","doi-asserted-by":"publisher","unstructured":"Chalaguine, L.A., & Hunter, A. (2020). A persuasive chatbot using a crowd-sourced argument graph and concerns. In Computational models of argument - proceedings of COMMA. (vol. 326. pp. 9\u201320) IOS Press https:\/\/doi.org\/10.3233\/FAIA200487","DOI":"10.3233\/FAIA200487"},{"key":"9692_CR69","doi-asserted-by":"publisher","unstructured":"Chalaguine, L.A., Hunter, A., Potts, H., & Hamilton, F. (2019). Impact of argument type and concerns in argumentation with a chatbot. In 31st IEEE international conference on tools with artificial intelligence ICTAI (pp. 1557\u20131562). IEEE. https:\/\/doi.org\/10.1109\/ICTAI.2019.00224","DOI":"10.1109\/ICTAI.2019.00224"},{"key":"9692_CR70","unstructured":"Charwat, G., Dvor\u00e1k, W., Gaggl, S. A., Wallner, J.P. and Woltran, S. (2013). Implementing abstract argumentation-a survey. Tech Rep: Institut Fur Information Systeme."},{"key":"9692_CR71","unstructured":"Chen, G., Cheng, L., Tuan, L.A., & Bing, L. (2023). Exploring the potential of large language models in computational argumentation. arXiv preprint arXiv:2311.09022"},{"key":"9692_CR72","doi-asserted-by":"crossref","unstructured":"Chen, Z., do Amarante, D.V., Donaldson, J., Jo, Y., & Park, J. (2022). Argument mining for review helpfulness prediction. In Proceedings of the 2022 conference on empirical methods in natural language processing (pp. 8914\u20138922). EMNLP 2022, Abu Dhabi, United Arab Emirates, December 7-11, 2022. Association for Computational Linguistics. https:\/\/aclanthology.org\/2022.emnlp-main.609","DOI":"10.18653\/v1\/2022.emnlp-main.609"},{"issue":"4","key":"9692_CR73","doi-asserted-by":"publisher","first-page":"293","DOI":"10.1017\/S0269888906001044","volume":"21","author":"CI Ches\u00f1evar","year":"2006","unstructured":"Ches\u00f1evar, C. I., McGinnis, J., Modgil, S.,\u00a0Rahwan, I., Reed, C., Simari, G.R., South, M., Vreeswijk, G., & Wilmott, S. (2006). Towards an argument interchange format. The Knowledge Engineering Review, 21(4), 293\u2013316.","journal-title":"The Knowledge Engineering Review"},{"key":"9692_CR74","unstructured":"Cialdini, R.B. (1993). Influence: The psychology of persuasion. Morrow"},{"key":"9692_CR75","doi-asserted-by":"publisher","unstructured":"Ciocarlan, A., Masthoff, J., & Oren, N. (2019). Actual persuasiveness: Impact of personality, age and gender on message type susceptibility. In Persuasive technology 14th international conference PERSUASIVE, proceedings (vol. 11433, pp. 283\u2013294) Springer. https:\/\/doi.org\/10.1007\/978-3-030-17287-9_23","DOI":"10.1007\/978-3-030-17287-9_23"},{"key":"9692_CR76","unstructured":"Clayton, J., & Gaizauskas, R. (2022). Predicting the presence of reasoning markers in argumentative text. In Proceedings of the 9th workshop on argument mining, ArgMining@COLING 2022, Online and in Gyeongju, Republic of Korea, international conference on computational linguistics October 12 - 17, 2022. (pp. 137\u2013142). https:\/\/aclanthology.org\/2022.argmining-1.13"},{"key":"9692_CR77","doi-asserted-by":"publisher","unstructured":"Cocarascu, O., & Toni, F. (2016). Argumentation for machine learning: A survey. In computational models of argument - proceedings of COMMA (vol. 287, pp. 219\u2013230). IOS Press. https:\/\/doi.org\/10.3233\/978-1-61499-686-6-219","DOI":"10.3233\/978-1-61499-686-6-219"},{"key":"9692_CR78","doi-asserted-by":"publisher","unstructured":"Cocarascu, O., & Toni, F. (2017). Identifying attack and support argumentative relations using deep learning. In Proceedings of the 2017 conference on empirical methods in natural language processing, EMNLP. (pp. 1374\u20131379). Association for Computational Linguistics. https:\/\/doi.org\/10.18653\/v1\/d17-1144","DOI":"10.18653\/v1\/d17-1144"},{"key":"9692_CR79","doi-asserted-by":"crossref","unstructured":"Cocarascu, O., Cabrio, E., Villata, S., & Toni, F. (2020). A dataset independent set of baselines for relation prediction in argument mining. CoRR abs\/2003.04970. https:\/\/arxiv.org\/abs\/2003.04970","DOI":"10.3233\/FAIA200490"},{"issue":"5","key":"9692_CR80","doi-asserted-by":"publisher","first-page":"513","DOI":"10.1017\/S0269888913000325","volume":"29","author":"A Cohen","year":"2014","unstructured":"Cohen, A., Gottifredi, S., Garc\u00eda, A. J.,\u00a0& Simari, G.R. (2014). A survey of different approaches to support in argumentation systems. The Knowledge Engineering Review, 29(5), 513\u2013550. https:\/\/doi.org\/10.1017\/S0269888913000325","journal-title":"The Knowledge Engineering Review"},{"key":"9692_CR81","doi-asserted-by":"publisher","first-page":"76","DOI":"10.1016\/j.ijar.2017.12.008","volume":"94","author":"A Cohen","year":"2018","unstructured":"Cohen, A., Parsons, S., Sklar, E. I.,\u00a0& McBurney, P. (2018). A characterization of types of support between structured arguments and their relationship with support in abstract argumentation. International Journal of Approximate Reasoning, 94, 76\u2013104. https:\/\/doi.org\/10.1016\/j.ijar.2017.12.008","journal-title":"International Journal of Approximate Reasoning"},{"key":"9692_CR82","doi-asserted-by":"crossref","unstructured":"Correia, M., Cruz, J., & Leite, J. (2014). On the efficient implementation of social abstract argumentation. In ECAI 2014. (pp. 225\u2013230). IOS Press.","DOI":"10.3233\/978-1-61499-419-0-225"},{"key":"9692_CR83","doi-asserted-by":"publisher","unstructured":"Coste-Marquis, S., Devred, C., & Marquis, P. (2005). Prudent semantics for argumentation frameworks. In 17th IEEE international conference on tools with artificial intelligence (ICTAI) (pp. 568\u2013572). IEEE Computer Society. https:\/\/doi.org\/10.1109\/ICTAI.2005.103","DOI":"10.1109\/ICTAI.2005.103"},{"key":"9692_CR84","doi-asserted-by":"publisher","unstructured":"Craandijk, D., & Bex, F. (2020). Deep learning for abstract argumentation semantics. In Proceedings of the 29th international joint conference on artificial intelligence (pp. 1667\u20131673). IJCAI. ijcai.org. https:\/\/doi.org\/10.24963\/ijcai.2020\/231","DOI":"10.24963\/ijcai.2020\/231"},{"key":"9692_CR85","doi-asserted-by":"crossref","unstructured":"Cramer, M., & Guillaume, M. (2018). Empirical cognitive study on abstract argumentation semantics. In Computational Models of Argument. (pp. 413\u2013424). IOS Press.","DOI":"10.3233\/978-1-61499-906-5-413"},{"key":"9692_CR86","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.artint.2015.12.004","volume":"233","author":"R Craven","year":"2016","unstructured":"Craven, R., & Toni, F. (2016). Argument graphs and assumption-based argumentation. Artificial Intelligence, 233, 1\u201359. https:\/\/doi.org\/10.1016\/j.artint.2015.12.004","journal-title":"Artificial Intelligence"},{"key":"9692_CR87","doi-asserted-by":"crossref","unstructured":"Damo, G., Ocampo, N.B., Cabrio, E., & Villata, S. (2024). Peace: Providing explanations and analysis for combating hate expressions. In 27th European conference on artificial intelligence.","DOI":"10.3233\/FAIA241029"},{"key":"9692_CR88","unstructured":"Delobelle, J. (2017). Ranking-based semantics for abstract argumentation. (s\u00e9mantique \u00e0 base de classement pour l\u2019argumentation abstraite). PhD thesis, Artois University, Arras, France, https:\/\/tel.archives-ouvertes.fr\/tel-01937279"},{"key":"9692_CR89","doi-asserted-by":"crossref","unstructured":"Dimopoulos, Y., Mailly, J., & Moraitis, P. (2018). Control argumentation frameworks. In Proceedings of the 32nd AAAI conference on artificial intelligence, (aaai-18), the 30th innovative applications of artificial intelligence (IAAI-18), and the 8th AAAI symposium on educational advances in artificial intelligence (EAAI-18), New Orleans, Louisiana, USA, February 2-7, 2018. (pp. 4678\u20134685). AAAI Press. https:\/\/www.aaai.org\/ocs\/index.php\/AAAI\/AAAI18\/paper\/view\/16639","DOI":"10.1609\/aaai.v32i1.11583"},{"key":"9692_CR90","doi-asserted-by":"publisher","unstructured":"Doder, D., Vesic, S., & Croitoru, M. (2020). Ranking semantics for argumentation systems with necessities. In Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, IJCAI. ijcai.org, pp 1912\u20131918, https:\/\/doi.org\/10.24963\/ijcai.2020\/265.","DOI":"10.24963\/ijcai.2020\/265"},{"key":"9692_CR91","doi-asserted-by":"crossref","unstructured":"Donadello, I., Hunter, A., Teso, S., & Dragoni, M. (2022). Machine learning for utility prediction in argument-based computational persuasion. In 36th AAAI conference on artificial intelligence, AAAI 2022, 34th conference on innovative applications of artificial intelligence, IAAI 2022, the 12th symposium on educational advances in artificial intelligence, EAAI 2022 Virtual Event, February 22 - March 1, 2022. (pp. 5592\u20135599). AAAI Press. https:\/\/ojs.aaai.org\/index.php\/AAAI\/article\/view\/20499","DOI":"10.1609\/aaai.v36i5.20499"},{"issue":"3","key":"9692_CR92","doi-asserted-by":"publisher","first-page":"223","DOI":"10.3233\/AAC-180425","volume":"9","author":"S Doutre","year":"2018","unstructured":"Doutre, S., & Mailly, J. (2018). Constraints and changes: A survey of abstract argumentation dynamics. Argument and Computation, 9(3), 223\u2013248. https:\/\/doi.org\/10.3233\/AAC-180425","journal-title":"Argument and Computation"},{"issue":"2","key":"9692_CR93","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1016\/0004-3702(94)00041-X","volume":"77","author":"PM Dung","year":"1995","unstructured":"Dung, P. M. (1995). On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games. Artificial Intelligence, 77(2), 321\u2013358. https:\/\/doi.org\/10.1016\/0004-3702(94)00041-X","journal-title":"Artificial Intelligence"},{"key":"9692_CR94","doi-asserted-by":"publisher","unstructured":"Dung, P.M., & Thang, P.M. (2010). Towards (probabilistic) argumentation for jury-based dispute resolution. In Computational models of argument: Proceedings of COMMA (vol 216. pp 171\u2013182). IOS Press. https:\/\/doi.org\/10.3233\/978-1-60750-619-5-171","DOI":"10.3233\/978-1-60750-619-5-171"},{"key":"9692_CR95","unstructured":"Dung, P.M., Mancarella, P., & Toni, F. (2006). A dialectic procedure for sceptical, assumption-based argumentation. In Computational models of argument: Proceedings of COMMA. (vol. 144, pp. 145\u2013156) IOS Press. http:\/\/www.booksonline.iospress.nl\/Content\/View.aspx?piid=1935"},{"key":"9692_CR96","doi-asserted-by":"publisher","unstructured":"Dunne, P.E., & Wooldridge, M.J. (2009). Complexity of abstract argumentation. In Argumentation in artificial intelligence (pp. 85\u2013104). Springer. https:\/\/doi.org\/10.1007\/978-0-387-98197-0_5","DOI":"10.1007\/978-0-387-98197-0_5"},{"issue":"2","key":"9692_CR97","doi-asserted-by":"publisher","first-page":"457","DOI":"10.1016\/j.artint.2010.09.005","volume":"175","author":"PE Dunne","year":"2011","unstructured":"Dunne, P. E., Hunter, A., McBurney, P.,\u00a0Parsons, S., & Wooldridge, M. (2011). Weighted argument systems: Basic definitions, algorithms, and complexity results. Artificial Intelligence, 175(2), 457\u2013486. https:\/\/doi.org\/10.1016\/j.artint.2010.09.005","journal-title":"Artificial Intelligence"},{"key":"9692_CR98","unstructured":"Durmus, E., & Cardie, C. (2019). Exploring the role of prior beliefs for argument persuasion. CoRR abs\/1906.11301. http:\/\/arxiv.org\/abs\/1906.11301"},{"key":"9692_CR99","doi-asserted-by":"publisher","unstructured":"Dusmanu, M., Cabrio, E., & Villata, S. (2017). Argument mining on twitter: Arguments, facts and sources. In Proceedings of the 2017 conference on empirical methods in natural language processing, EMNLP (pp 2317\u20132322). Association for Computational Linguistics. https:\/\/doi.org\/10.18653\/v1\/d17-1245","DOI":"10.18653\/v1\/d17-1245"},{"key":"9692_CR100","unstructured":"Dvor\u00e1k, W., K\u00f6nig, M., Wallner, J.P., & Woltran, S. (2021). Aspartix-v21. CoRR abs\/2109.03166. arxiv:2109.03166"},{"key":"9692_CR101","doi-asserted-by":"crossref","unstructured":"Dycke, N., Kuznetsov, I., & Gurevych, I. (2023). Overview of pragtag-2023: Low-resource multi-domain pragmatic tagging of peer reviews. In Proceedings of the 10th workshop on argument Mining (pp. 187\u2013196).","DOI":"10.18653\/v1\/2023.argmining-1.21"},{"key":"9692_CR102","doi-asserted-by":"crossref","unstructured":"Eemeren van, F. H. (2001). Crucial concepts in argumentation theory. Amsterdam University Press.","DOI":"10.5117\/9789053565230"},{"key":"9692_CR103","doi-asserted-by":"publisher","unstructured":"Egawa, R., Morio, G., & Fujita, K. (2019). Annotating and analyzing semantic role of elementary units and relations in online persuasive arguments. In Proceedings of the 57th conference of the association for computational linguistics, ACL. (pp. 422\u2013428). Association for Computational Linguistics. https:\/\/doi.org\/10.18653\/v1\/p19-2059","DOI":"10.18653\/v1\/p19-2059"},{"key":"9692_CR104","doi-asserted-by":"publisher","unstructured":"Eger, S., Daxenberger, J., & Gurevych, I. (2017). Neural end-to-end learning for computational argumentation mining. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, ACL (pp. 11\u201322). Association for Computational Linguistics. https:\/\/doi.org\/10.18653\/v1\/P17-1002","DOI":"10.18653\/v1\/P17-1002"},{"key":"9692_CR105","unstructured":"Eger, S., Daxenberger, J., Stab, C., & Gurevych, I. (2018a). Cross-lingual argumentation mining: Machine translation (and a bit of projection) is all you need! In Proceedings of the 27th international conference on computational linguistics, COLING. (pp 831\u2013844). Association for Computational Linguistics. https:\/\/aclanthology.org\/C18-1071\/"},{"key":"9692_CR106","doi-asserted-by":"crossref","unstructured":"E\u011filmez, S., Martins, J., & Leite, J. (2013). Extending social abstract argumentation with votes on attacks. InInternational workshop on theorie and applications of formal argumentation. (pp. 16\u201331). Springer.","DOI":"10.1007\/978-3-642-54373-9_2"},{"key":"9692_CR107","doi-asserted-by":"publisher","unstructured":"Evripidou, V., & Toni, F. (2012). Argumentation and voting for an intelligent user empowering business directory on the web. In Web reasoning and rule systems - 6th international conference, RR (vol. 7497, pp. 16\u201331). Springer. https:\/\/doi.org\/10.1007\/978-3-642-33203-6_16","DOI":"10.1007\/978-3-642-33203-6_16"},{"issue":"4","key":"9692_CR108","doi-asserted-by":"publisher","first-page":"427","DOI":"10.1177\/0741088388005004002","volume":"5","author":"J Fahnestock","year":"1988","unstructured":"Fahnestock, J., & Secor, M. (1988). The stases in scientific and literary argument. Written communication, 5(4), 427\u2013443.","journal-title":"Written communication"},{"key":"9692_CR109","doi-asserted-by":"publisher","unstructured":"Fazzinga, B., Flesca, S., & Furfaro, F. (2018). Probabilistic bipolar abstract argumentation frameworks: Complexity results. In Proceedings of the 27th international joint conference on artificial intelligence (pp. 1803\u20131809). IJCAI. ijcai.org. https:\/\/doi.org\/10.24963\/ijcai.2018\/249","DOI":"10.24963\/ijcai.2018\/249"},{"key":"9692_CR110","unstructured":"Feng, V.W., & Hirst, G. (2014). Two-pass discourse segmentation with pairing and global features. CoRR abs\/1407.8215. http:\/\/arxiv.org\/abs\/1407.8215."},{"key":"9692_CR111","unstructured":"Fisher, S., & Roark, B. (2007). The utility of parse-derived features for automatic discourse segmentation. In ACL Proceedings of the 45th annual meeting of the association for computational linguistics. The Association for Computational Linguistics. https:\/\/aclanthology.org\/P07-1062\/"},{"key":"9692_CR112","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2019.103193","author":"SA Gaggl","year":"2020","unstructured":"Gaggl, S.A., Linsbichler, T., Maratea, M., & Woltran, S.\u00a0(2020). Design and results of the second international competition on computational models of argumentation. Artificial Intelligence. https:\/\/doi.org\/10.1016\/j.artint.2019.103193","journal-title":"Artificial Intelligence"},{"key":"9692_CR113","unstructured":"Gaignier, F., Dimopoulos, Y., Mailly, J.G., & Moraitis, P. (2021) Probabilistic control argumentation frameworks. In AAMAS \u201921: 20th international conference on autonomous agents and multiagent systems, virtual event, United Kingdom May 3-7, 2021. (pp. 519\u2013527). ACM. https:\/\/www.ifaamas.org\/Proceedings\/aamas2021\/pdfs\/p519.pdf"},{"issue":"1\u20132","key":"9692_CR114","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1017\/S1471068403001674","volume":"4","author":"AJ Garc\u00eda","year":"2004","unstructured":"Garc\u00eda, A. J., & Simari, G. R. (2004). Defeasible logic programming: An argumentative approach. Theory and practice of logic programming, 4(1\u20132), 95\u2013138. https:\/\/doi.org\/10.1017\/S1471068403001674","journal-title":"Theory and practice of logic programming"},{"key":"9692_CR115","doi-asserted-by":"crossref","unstructured":"Gemechu, D., Ruiz-Dolz, R., & Reed, C. (2024). Aries: A general benchmark for argument relation identification. In Proceedings of the 11th workshop on argument mining (ArgMining 2024). (pp. 1\u201314).","DOI":"10.18653\/v1\/2024.argmining-1.1"},{"key":"9692_CR116","doi-asserted-by":"crossref","unstructured":"Georgila, K., & Traum, D.R. (2011). Reinforcement learning of argumentation dialogue policies in negotiation. In INTERSPEECH, 12th annual conference of the international speech communication association (pp. 2073\u20132076). ISCA. http:\/\/www.isca-speech.org\/archive\/interspeech_2011\/i11_2073.html","DOI":"10.21437\/Interspeech.2011-544"},{"key":"9692_CR117","doi-asserted-by":"publisher","DOI":"10.1075\/tsl.3","volume-title":"Topic continuity in discourse","author":"T Giv\u00f3n","year":"1983","unstructured":"Giv\u00f3n, T. (1983). Topic continuity in discourse. John Benjamins."},{"key":"9692_CR118","doi-asserted-by":"publisher","unstructured":"Gleize, M., Shnarch, E., Choshen, L., Dankin, L., Moshkowich, G., Aharonov, R., & Slonim, N. (2019). Are you convinced? Choosing the more convincing evidence with a siamese network. In Proceedings of the 57th conference of the association for computational linguistics, ACL. (pp. 967\u2013976). Association for Computational Linguistics. https:\/\/doi.org\/10.18653\/v1\/p19-1093","DOI":"10.18653\/v1\/p19-1093"},{"key":"9692_CR119","unstructured":"Gorur, D., Rago, A., & Toni, F. (2024). Can large language models perform relation-based argument mining? arXiv preprint arXiv:2402.11243"},{"key":"9692_CR120","doi-asserted-by":"publisher","unstructured":"Goudas, T., Louizos, C., Petasis, G., & Karkaletsis, V. (2014). Argument extraction from news, blogs, and social media. In Artificial intelligence: Methods and applications - 8th hellenic conference on AI, SETN (vol. 8445, pp. 287\u2013299) Springer. https:\/\/doi.org\/10.1007\/978-3-319-07064-3_23","DOI":"10.1007\/978-3-319-07064-3_23"},{"issue":"2","key":"9692_CR121","doi-asserted-by":"publisher","first-page":"121","DOI":"10.3233\/AAC-180038","volume":"9","author":"NL Green","year":"2018","unstructured":"Green, N. L. (2018). Towards mining scientific discourse using argumentation schemes. Argument & Computation, 9(2), 121\u2013135.","journal-title":"Argument & Computation"},{"key":"9692_CR122","doi-asserted-by":"crossref","unstructured":"Gretz, S., Bilu, Y., Cohen-Karlik, E., & Slonim, N. (2020a). The workweek is the best time to start a family \u2013 a study of gpt-2 based claim generation. arXiv:2010.06185","DOI":"10.18653\/v1\/2020.findings-emnlp.47"},{"key":"9692_CR123","doi-asserted-by":"crossref","unstructured":"Gretz, S., Friedman, R., Cohen-Karlik, E., Toledo, A., Lahav, D., Aharonov, R., & Slonim, N. (2020b). A large-scale dataset for argument quality ranking: Construction and analysis. In The Thirty-Fourth AAAI conference on artificial intelligence. (pp. 7805\u20137813). AAAI Press. https:\/\/aaai.org\/ojs\/index.php\/AAAI\/article\/view\/6285","DOI":"10.1609\/aaai.v34i05.6285"},{"key":"9692_CR124","unstructured":"Grimes, J.E. (1972). The Thread of Discourse. ERIC."},{"key":"9692_CR125","doi-asserted-by":"publisher","unstructured":"Haddadan, S., Cabrio, E., & Villata, S. (2019). Yes, we can! mining arguments in 50 years of US presidential campaign debates. In Proceedings of the 57th conference of the association for computational linguistics, ACL. (pp. 4684\u20134690) Association for Computational Linguistics. https:\/\/doi.org\/10.18653\/v1\/p19-1463","DOI":"10.18653\/v1\/p19-1463"},{"key":"9692_CR126","unstructured":"Hadjinikolis, C., Siantos, Y., Modgil, S., Black, E., & McBurney, P. (2013). Opponent modelling in persuasion dialogues. In IJCAI, proceedings of the 23rd international joint conference on artificial intelligence (pp. 164\u2013170). IJCAI\/AAAI. http:\/\/www.aaai.org\/ocs\/index.php\/IJCAI\/IJCAI13\/paper\/view\/6834"},{"issue":"2","key":"9692_CR127","doi-asserted-by":"publisher","first-page":"113","DOI":"10.3233\/AAC-191007","volume":"10","author":"E Hadoux","year":"2019","unstructured":"Hadoux, E., & Hunter, A. (2019). Comfort or safety? Gathering and using the concerns of a participant for better persuasion. Argument & Computation, 10(2), 113\u2013147. https:\/\/doi.org\/10.3233\/AAC-191007","journal-title":"Argument & Computation"},{"key":"9692_CR128","unstructured":"Heinisch, P., Frank, A., Opitz, J., Plenz, M., & Cimiano, P. (2022). Overview of the 2022 validity and novelty prediction shared task. In Proceedings of the 9th Workshop on Argument Mining (pp. 84\u201394)."},{"key":"9692_CR129","doi-asserted-by":"publisher","unstructured":"Hidey, C., & McKeown, K. (2019). Fixed that for you: Generating contrastive claims with semantic edits. In Proceedings of the 2019 conference of the North American chapter of the association for computational linguistics. (pp. 1756\u20131767). Association for Computational Linguistics. https:\/\/doi.org\/10.18653\/v1\/n19-1174","DOI":"10.18653\/v1\/n19-1174"},{"key":"9692_CR130","doi-asserted-by":"publisher","unstructured":"Hou Y, Jochim C (2017) Argument relation classification using a joint inference model. In Proceedings of the 4th workshop on argument mining, ArgMining@EMNLP (pp. 60\u201366). Association for Computational Linguistics. https:\/\/doi.org\/10.18653\/v1\/w17-5107","DOI":"10.18653\/v1\/w17-5107"},{"key":"9692_CR131","doi-asserted-by":"publisher","unstructured":"Hsiao, F.H., Yen, A.Z., Huang, H.H., & Chen, H.H. (2022). Modeling inter round attack of online debaters for winner prediction. In WWW \u201922: the ACM web conference 2022, virtual event Lyon, France, April 25 - 29, 2022. (pp. 2860\u20132869) ACM. https:\/\/doi.org\/10.1145\/3485447.3512006","DOI":"10.1145\/3485447.3512006"},{"key":"9692_CR132","doi-asserted-by":"crossref","unstructured":"Hua, X., & Wang, L. (2018). Neural argument generation augmented with externally retrieved evidence. In Proceedings of the 56th annual meeting of the association for computational linguistics, ACL. (pp. 219\u2013230). Association for Computational Linguistics. https:\/\/aclanthology.org\/P18-1021\/","DOI":"10.18653\/v1\/P18-1021"},{"key":"9692_CR133","doi-asserted-by":"publisher","unstructured":"Hua, X., Hu, Z., & Wang, L. (2019). Argument generation with retrieval, planning, and realization. In Proceedings of the 57th conference of the association for computational linguistics, ACL. (pp. 2661\u20132672). Association for Computational Linguistics. https:\/\/doi.org\/10.18653\/v1\/p19-1255","DOI":"10.18653\/v1\/p19-1255"},{"key":"9692_CR134","doi-asserted-by":"publisher","unstructured":"Hunter, A. (2012). Some foundations for probabilistic abstract argumentation. In Computational models of argument - proceedings of COMMA (vol. 245. pp. 117\u2013128). IOS Press. https:\/\/doi.org\/10.3233\/978-1-61499-111-3-117","DOI":"10.3233\/978-1-61499-111-3-117"},{"key":"9692_CR135","doi-asserted-by":"crossref","unstructured":"Hunter, A. (2016). Persuasion dialogues via restricted interfaces using probabilistic argumentation. In Scalable Uncertainty Management: 10th International Conference, SUM 2016 Proceedings 10 Nice, France, September 21-23, 2016. (pp. 184\u2013198). Springer.","DOI":"10.1007\/978-3-319-45856-4_13"},{"key":"9692_CR136","doi-asserted-by":"crossref","unstructured":"Hunter, A. (2020). Generating instantiated argument graphs from probabilistic information. In ECAI - 24th European conference on artificial intelligence (pp. 769\u2013776). IOS Press.","DOI":"10.3233\/FAIA200165"},{"key":"9692_CR137","doi-asserted-by":"publisher","first-page":"565","DOI":"10.1613\/jair.5393","volume":"59","author":"A Hunter","year":"2017","unstructured":"Hunter, A., & Thimm, M. (2017). Probabilistic reasoning with abstract argumentation frameworks. Journal of Artificial Intelligence Research, 59, 565\u2013611. https:\/\/doi.org\/10.1613\/jair.5393","journal-title":"Journal of Artificial Intelligence Research"},{"key":"9692_CR138","doi-asserted-by":"publisher","unstructured":"Hunter, A., Chalaguine, L., Czernuszenko, T., Hadoux, E., & Polberg, S. (2019). Towards computational persuasion via natural language argumentation dialogues. In KI: Advances in artificial intelligence - 42nd German conference on ai, proceedings (vol. 11793, pp 18\u201333). Springer. https:\/\/doi.org\/10.1007\/978-3-030-30179-8_2","DOI":"10.1007\/978-3-030-30179-8_2"},{"key":"9692_CR139","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2020.103236","volume":"281","author":"A Hunter","year":"2020","unstructured":"Hunter, A., Polberg, S., & Thimm, M. (2020). Epistemic graphs for representing and reasoning with positive and negative influences of arguments. Artificial Intelligence, 281, 103236.","journal-title":"Artificial Intelligence"},{"key":"9692_CR140","doi-asserted-by":"publisher","unstructured":"Jaradat, I., Gencheva, P., Barr\u00f3n-Cede\u00f1o, A., M\u00e0rquez, L., & Nakov, P. (2018). Claimrank: Detecting check-worthy claims in Arabic and English. In Proceedings of the 2018 conference of the north american chapter of the association for computational linguistics. (pp. 26\u201330). Association for Computational Linguistics. https:\/\/doi.org\/10.18653\/v1\/n18-5006","DOI":"10.18653\/v1\/n18-5006"},{"key":"9692_CR141","doi-asserted-by":"publisher","unstructured":"Jo, Y., Visser, J., Reed, C., & Hovy, E. (2019). A cascade model for proposition extraction in argumentation. In Proceedings of the 6th Workshop on Argument Mining, ArgMining@ACL. Association for Computational Linguistics. https:\/\/doi.org\/10.18653\/v1\/w19-4502","DOI":"10.18653\/v1\/w19-4502"},{"key":"9692_CR142","doi-asserted-by":"publisher","first-page":"721","DOI":"10.1162\/tacl_a_00394","volume":"9","author":"Y Jo","year":"2021","unstructured":"Jo, Y., Bang, S., Reed, C., & Hovy, E.\u00a0(2021). Classifying argumentative relations using logical mechanisms and argumentation schemes. Transactions of the Association for Computational Linguistics, 9, 721\u2013739.","journal-title":"Transactions of the Association for Computational Linguistics"},{"key":"9692_CR143","unstructured":"Joty, S.R., Carenini, G., & Ng, R.T. (2012). A novel discriminative framework for sentence-level discourse analysis. In Proceedings of the 2012 joint conference on empirical methods in natural language processing EMNLP. (pp. 904\u2013915). ACL https:\/\/aclanthology.org\/D12-1083\/"},{"key":"9692_CR144","doi-asserted-by":"publisher","unstructured":"Kampik, T., Gabbay, D.M., & Sartor, G. (2021). The burden of persuasion in abstract argumentation. In Logic and Argumentation - 4th International Conference, CLAR 2021, Hangzhou, China, October 20-22, 2021, Proceedings, Lecture Notes in Computer Science. (vol. 13040. pp. 224\u2013243). Springer. https:\/\/doi.org\/10.1007\/978-3-030-89391-0_13","DOI":"10.1007\/978-3-030-89391-0_13"},{"key":"9692_CR145","doi-asserted-by":"publisher","unstructured":"Al Khatib, K., V\u00f6lske, M., Syed, S., Kolyada, N., & Stein, B. (2020). Exploiting personal characteristics of debaters for predicting persuasiveness. In Proceedings of the 58th annual meeting of the association for computational linguistics, ACL. (pp. 7067\u20137072). Association for Computational Linguistics. https:\/\/doi.org\/10.18653\/v1\/2020.acl-main.632","DOI":"10.18653\/v1\/2020.acl-main.632"},{"key":"9692_CR146","unstructured":"Lagniez, J.M., Lonca, E., Mailly, J.G., & Rossit, J. (2020). Introducing the fourth international competition on computational models of argumentation. In Proceedings of the 3rd international workshop on systems and algorithms for formal argumentation co-located with (COMMA). (vol. 2672. pp. 80\u201385). CEUR-WS.org .http:\/\/ceur-ws.org\/Vol-2672\/paper_9.pdf"},{"key":"9692_CR147","unstructured":"Lagniez, J.M., Lonca, E., Mailly, J.G., & Rossit, J. (2021). Design and results of ICCMA 2021. CoRR abs\/2109.08884. arxiv:2109.08884"},{"key":"9692_CR148","doi-asserted-by":"crossref","unstructured":"Lawrence, J., & Reed, C. (2016). Argument mining using argumentation scheme structures. In Computational Models of Argument (pp. 379\u2013390). IOS Press.","DOI":"10.3233\/978-1-61499-686-6-379"},{"issue":"4","key":"9692_CR149","doi-asserted-by":"publisher","first-page":"765","DOI":"10.1162\/coli_a_00364","volume":"45","author":"J Lawrence","year":"2019","unstructured":"Lawrence, J., & Reed, C. (2019). Argument mining: A survey. Linguistics Computational, 45(4), 765\u2013818. https:\/\/doi.org\/10.1162\/coli_a_00364","journal-title":"Linguistics Computational"},{"key":"9692_CR150","doi-asserted-by":"publisher","unstructured":"Lawrence, J., Reed, C., Allen, C., McAlister, S., & Ravenscroft, A. (2014). Mining arguments from 19th century philosophical texts using topic based modelling. In Proceedings of the first workshop on argument mining ArgMining@ACL. (pp. 79\u201387) The Association for Computer Linguistics. https:\/\/doi.org\/10.3115\/v1\/w14-2111","DOI":"10.3115\/v1\/w14-2111"},{"key":"9692_CR151","doi-asserted-by":"publisher","unstructured":"Le, D., Nguyen, C., & Nguyen, K.A. (2018). Dave the debater: A retrieval-based and generative argumentative dialogue agent. In Proceedings of the 5th workshop on argument mining, ArgMining@EMNLP (pp. 121\u2013130). Association for Computational Linguistics. https:\/\/doi.org\/10.18653\/v1\/w18-5215","DOI":"10.18653\/v1\/w18-5215"},{"key":"9692_CR152","unstructured":"Leite, J., & Martins, J. (2011). Social abstract argumentation. In 22nd International joint conference on artificial intelligence."},{"key":"9692_CR153","unstructured":"Levy, R., Bilu, Y., Hershcovich, D., Aharoni, E., & Slonim, N. (2014). Context dependent claim detection. In COLING: Technical papers. ACL (pp. 1489\u20131500). https:\/\/aclanthology.org\/C14-1141\/"},{"key":"9692_CR154","doi-asserted-by":"publisher","unstructured":"Levy, R., Gretz, S., Sznajder, B., Hummel, S., Aharonov, R., & Slonim, N. (2017). Unsupervised corpus-wide claim detection. In Proceedings of the 4th Workshop on Argument Mining, ArgMining@EMNLP. (pp. 79\u201384). Association for Computational Linguistics. https:\/\/doi.org\/10.18653\/v1\/w17-5110","DOI":"10.18653\/v1\/w17-5110"},{"key":"9692_CR155","doi-asserted-by":"publisher","unstructured":"Li, H., Oren, N., & Norman, T.J. (2011). Probabilistic argumentation frameworks. In Theorie and applications of formal argumentation - first international workshop, TAFA (vol. 7132, pp. 1\u201316). Springer. https:\/\/doi.org\/10.1007\/978-3-642-29184-5_1","DOI":"10.1007\/978-3-642-29184-5_1"},{"key":"9692_CR156","unstructured":"Li, Y., Chen, W., Wei, Z., Huang, Y., Wang, C., Wang, S., Zhang, Q., Huang, X.J., & Wu, L. (2022). A structure-aware argument encoder for literature discourse analysis. In Proceedings of the 29th international conference on computational linguistics. international committee on computational linguistics, COLING 2022 (pp. 7093\u20137098). Gyeongju, Republic of Korea, October 12-17, 2022. https:\/\/aclanthology.org\/2022.coling-1.619"},{"issue":"11","key":"9692_CR157","doi-asserted-by":"publisher","first-page":"1790","DOI":"10.1016\/j.artint.2011.03.006","volume":"175","author":"BS Liao","year":"2011","unstructured":"Liao, B. S., Jin, L., & Koons, R. C. (2011). Dynamics of argumentation systems: A division-based method. Artificial Intelligence, 175(11), 1790\u20131814. https:\/\/doi.org\/10.1016\/j.artint.2011.03.006","journal-title":"Artificial Intelligence"},{"key":"9692_CR158","doi-asserted-by":"crossref","unstructured":"Liu, Z., Elaraby, M., Zhong, Y., & Litman, D. (2023). Overview of imagearg-2023: The first shared task in multimodal argument mining. In Proceedings of the 10th workshop on argument mining (pp. 120\u2013132).","DOI":"10.18653\/v1\/2023.argmining-1.12"},{"key":"9692_CR159","doi-asserted-by":"publisher","unstructured":"Lukin, S.M., Anand, P., Walker, M., & Whittaker, S. (2017). Argument strength is in the eye of the beholder: Audience effects in persuasion. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics, EACL. (pp. 742\u2013753). Association for Computational Linguistics. https:\/\/doi.org\/10.18653\/v1\/e17-1070","DOI":"10.18653\/v1\/e17-1070"},{"issue":"2","key":"9692_CR160","doi-asserted-by":"publisher","first-page":"146","DOI":"10.58680\/ccc197916236","volume":"30","author":"AA Lunsford","year":"1979","unstructured":"Lunsford, A. A. (1979). Aristotelian vs. rogerian argument: A reassessment. College Composition and Communication, 30(2), 146\u2013151.","journal-title":"College Composition and Communication"},{"key":"9692_CR161","unstructured":"Madnani, N., Heilman, M., Tetreault, J., & Chodorow, M. (2012). Identifying high-level organizational elements in argumentative discourse. In Human language technologies: Conference of the north american chapter of the association of computational linguistics (pp. 20\u201328). The Association for Computational Linguistics. https:\/\/aclanthology.org\/N12-1003\/"},{"key":"9692_CR162","doi-asserted-by":"publisher","unstructured":"Mayer, T., Cabrio, E., & Villata, S. (2018). Evidence type classification in randomized controlled trials. In proceedings of the 5th workshop on argument mining, argmining@emnlp (pp. 29\u201334). Association for Computational Linguistics. https:\/\/doi.org\/10.18653\/v1\/w18-5204","DOI":"10.18653\/v1\/w18-5204"},{"key":"9692_CR163","doi-asserted-by":"publisher","unstructured":"Mayer, T., Cabrio, E., & Villata, S. (2020). Transformer-based argument mining for healthcare applications. In ECAI 2020 - 24th European Conference on Artificial Intelligence (vol. 325, pp. 2108\u20132115). IOS Press. https:\/\/doi.org\/10.3233\/FAIA200334","DOI":"10.3233\/FAIA200334"},{"key":"9692_CR164","doi-asserted-by":"crossref","unstructured":"Menini, S., Cabrio, E., Tonelli, S., & Villata, S. (2018). Never retreat, never retract: Argumentation analysis for political speeches. In Proceedings of the thirty-second AAAI conference on artificial intelligence, (AAAI-18) (pp. 4889\u20134896). AAAI Press. https:\/\/www.aaai.org\/ocs\/index.php\/AAAI\/AAAI18\/paper\/view\/16393","DOI":"10.1609\/aaai.v32i1.11920"},{"issue":"9\u201310","key":"9692_CR165","doi-asserted-by":"publisher","first-page":"901","DOI":"10.1016\/j.artint.2009.02.001","volume":"173","author":"S Modgil","year":"2009","unstructured":"Modgil, S. (2009). Reasoning about preferences in argumentation frameworks. Artificial Intelligence, 173(9\u201310), 901\u2013934. https:\/\/doi.org\/10.1016\/j.artint.2009.02.001","journal-title":"Artificial Intelligence"},{"key":"9692_CR166","unstructured":"Modgil, S., & Bench-Capon, T. (2010). Integrating dialectical and accrual modes of argumentation. In Computational models of argument (pp. 335\u2013346). IOS Press."},{"issue":"6","key":"9692_CR167","doi-asserted-by":"publisher","first-page":"959","DOI":"10.1093\/logcom\/exq054","volume":"21","author":"S Modgil","year":"2011","unstructured":"Modgil, S., & Bench-Capon, T. J. (2011). Metalevel argumentation. Journal of Logic and Computation, 21(6), 959\u20131003.","journal-title":"Journal of Logic and Computation"},{"key":"9692_CR168","doi-asserted-by":"crossref","unstructured":"Modgil, S., & D\u2019Agostino, M. (2020). A fully rational account of structured argumentation under resource bounds. In Proceedings of the 29th international joint conference on artificial intelligence main track., international joint conferences on artificial intelligence (pp. 1841\u20131847).","DOI":"10.24963\/ijcai.2020\/255"},{"key":"9692_CR169","doi-asserted-by":"publisher","first-page":"361","DOI":"10.1016\/j.artint.2012.10.008","volume":"195","author":"S Modgil","year":"2013","unstructured":"Modgil, S., & Prakken, H. (2013). A general account of argumentation with preferences. Artificial Intelligence, 195, 361\u2013397.","journal-title":"Artificial Intelligence"},{"issue":"1","key":"9692_CR170","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1080\/19462166.2013.869766","volume":"5","author":"S Modgil","year":"2014","unstructured":"Modgil, S., & Prakken, H. (2014). The aspic+ framework for structured argumentation: A tutorial. Argument & Computation, 5(1), 31\u201362. https:\/\/doi.org\/10.1080\/19462166.2013.869766","journal-title":"Argument & Computation"},{"key":"9692_CR171","doi-asserted-by":"publisher","unstructured":"Moens, M.F., Boiy, E., Palau, R.M., & Reed, C. (2007). Automatic detection of arguments in legal texts. In The 11th international conference on artificial intelligence and law, ACM. (pp. 225\u2013230). https:\/\/doi.org\/10.1145\/1276318.1276362","DOI":"10.1145\/1276318.1276362"},{"issue":"6","key":"9692_CR172","doi-asserted-by":"publisher","first-page":"2182","DOI":"10.1016\/j.eswa.2012.10.045","volume":"40","author":"A Monteserin","year":"2013","unstructured":"Monteserin, A., & Amandi, A. (2013). A reinforcement learning approach to improve the argument selection effectiveness in argumentation-based negotiation. Expert Systems with Applications, 40(6), 2182\u20132188. https:\/\/doi.org\/10.1016\/j.eswa.2012.10.045","journal-title":"Expert Systems with Applications"},{"key":"9692_CR173","doi-asserted-by":"publisher","unstructured":"Morio, G., & Fujita, K. (2018). End-to-end argument mining for discussion threads based on parallel constrained pointer architecture. In Proceedings of the 5th workshop on argument mining, ArgMining@EMNLP. (pp. 11\u201321). Association for Computational Linguistics. https:\/\/doi.org\/10.18653\/v1\/w18-5202","DOI":"10.18653\/v1\/w18-5202"},{"key":"9692_CR174","doi-asserted-by":"publisher","unstructured":"Morio, G., & Fujita, K. (2019). Syntactic graph convolution in multi-task learning for identifying and classifying the argument component. In 13th IEEE international conference on semantic computing, ICSC (pp. 271\u2013278) IEEE. https:\/\/doi.org\/10.1109\/ICOSC.2019.8665505","DOI":"10.1109\/ICOSC.2019.8665505"},{"key":"9692_CR175","doi-asserted-by":"publisher","first-page":"639","DOI":"10.1162\/tacl_a_00481","volume":"10","author":"G Morio","year":"2022","unstructured":"Morio, G., Ozaki, H., Morishita, T., & Yanai, K. (2022). End-to-end argument mining with cross-corpora multi-task learning. Transactions of the Association for Computational Linguistics, 10, 639\u2013658. https:\/\/doi.org\/10.1162\/tacl_a_00481","journal-title":"Transactions of the Association for Computational Linguistics"},{"key":"9692_CR176","doi-asserted-by":"publisher","unstructured":"Naderi, N., & Hirst, G. (2015). Argumentation mining in parliamentary discourse. In Principles and practice of multi-agent systems - international workshops: CMNA XV (vol. 9935, pp. 16\u201325). Springer. https:\/\/doi.org\/10.1007\/978-3-319-46218-9_2","DOI":"10.1007\/978-3-319-46218-9_2"},{"key":"9692_CR177","doi-asserted-by":"crossref","unstructured":"Naderi, N., & Hirst, G. (2018). Automated fact-checking of claims in argumentative parliamentary debates. In Proceedings of the first workshop on fact extraction and VERification (FEVER) (pp. 60\u201365).","DOI":"10.18653\/v1\/W18-5509"},{"key":"9692_CR178","doi-asserted-by":"crossref","unstructured":"Nguyen, H.V., & Litman, D.J. (2018). Argument mining for improving the automated scoring of persuasive essays. In Proceedings of the 32nd AAAI conference on artificial intelligence (pp. 5892\u20135899). AAAI Press. https:\/\/www.aaai.org\/ocs\/index.php\/AAAI\/AAAI18\/paper\/view\/16447.","DOI":"10.1609\/aaai.v32i1.12046"},{"key":"9692_CR179","doi-asserted-by":"publisher","unstructured":"Niculae, V., Park, J., & Cardie, C. (2017). Argument mining with structured svms and rnns. In Proceedings of the 55th annual meeting of the association for computational linguistics, ACL (pp. 985\u2013995). Association for Computational Linguistics. https:\/\/doi.org\/10.18653\/v1\/P17-1091","DOI":"10.18653\/v1\/P17-1091"},{"key":"9692_CR180","doi-asserted-by":"publisher","unstructured":"Niskanen, A., & J\u00e4rvisalo, M. (2020). Algorithms for dynamic argumentation frameworks: An incremental sat-based approach. In ECAI - 24th European conference on artificial intelligence (vol. 325, pp. 849\u2013856). IOS Press. https:\/\/doi.org\/10.3233\/FAIA200175","DOI":"10.3233\/FAIA200175"},{"key":"9692_CR181","first-page":"353","volume-title":"Defeasible logic","author":"D Nute","year":"1994","unstructured":"Nute, D. (1994). Defeasible logic (pp. 353\u2013395). Oxford University Press Inc."},{"key":"9692_CR182","doi-asserted-by":"publisher","unstructured":"Orbach, M., Bilu, Y., Gera, A., Kantor, Y., Dankin, L., Lavee, T., Kotlerman, L., Mirkin, S., Jacovi, M., Aharonov, R., & Slonim, N. (2019). A dataset of general-purpose rebuttal. In Proceedings of the 2019 conference on empirical methods in natural language ProcessingEMNLP (pp. 5590\u20135600). Association for Computational Linguistics. https:\/\/doi.org\/10.18653\/v1\/D19-1561","DOI":"10.18653\/v1\/D19-1561"},{"key":"9692_CR183","doi-asserted-by":"publisher","unstructured":"Ouerdane, W., Maudet, N., & Tsouki\u00e0s, A. (2010). Argumentation theory and decision aiding. In Trends in multiple criteria decision analysis. (pp. 177\u2013208) Springer. https:\/\/doi.org\/10.1007\/978-1-4419-5904-1_7","DOI":"10.1007\/978-1-4419-5904-1_7"},{"key":"9692_CR184","doi-asserted-by":"publisher","unstructured":"Palau, R.M., & Moens, M. (2009). Argumentation mining: The detection, classification and structure of arguments in text. In The 12th international conference on artificial intelligence and law, proceedings (pp. 98\u2013107). ACM. https:\/\/doi.org\/10.1145\/1568234.1568246","DOI":"10.1145\/1568234.1568246"},{"issue":"1","key":"9692_CR185","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10506-010-9104-x","volume":"19","author":"RM Palau","year":"2011","unstructured":"Palau, R. M., & Moens, M. (2011). Argumentation mining. Artificial Intelligence and Law, 19(1), 1\u201322. https:\/\/doi.org\/10.1007\/s10506-010-9104-x","journal-title":"Artificial Intelligence and Law"},{"key":"9692_CR186","doi-asserted-by":"publisher","unstructured":"Papangelis, A., & Georgila, K. (2015). Reinforcement learning of multi-issue negotiation dialogue policies. In Proceedings of the SIGDIAL conference (pp. 154\u2013158). The Association for Computer Linguistics. https:\/\/doi.org\/10.18653\/v1\/w15-4621","DOI":"10.18653\/v1\/w15-4621"},{"key":"9692_CR187","doi-asserted-by":"publisher","unstructured":"Park, J., & Cardie, C. (2014). Identifying appropriate support for propositions in online user comments. In Proceedings of the first workshop on argument mining, ArgMining@ACL (pp. 29\u201338 ). The Association for Computer Linguistic. https:\/\/doi.org\/10.3115\/v1\/w14-2105","DOI":"10.3115\/v1\/w14-2105"},{"key":"9692_CR188","unstructured":"Park, J., & Cardie, C. (2018). A corpus of erulemaking user comments for measuring evaluability of arguments. In Proceedings of the 11th international conference on language resources and evaluation, LREC. European Language Resources Association (ELRA). http:\/\/www.lrec-conf.org\/proceedings\/lrec2018\/summaries\/679.html"},{"issue":"3","key":"9692_CR189","doi-asserted-by":"publisher","first-page":"261","DOI":"10.1093\/logcom\/8.3.261","volume":"8","author":"S Parsons","year":"1998","unstructured":"Parsons, S., Sierra, C., & Jennings, N. (1998). Agents that reason and negotiate by arguing. Journal of Logic and Computation, 8(3), 261\u2013292.","journal-title":"Journal of Logic and Computation"},{"key":"9692_CR190","doi-asserted-by":"publisher","unstructured":"Patwari, A., Goldwasser, D., & Bagchi. S. (2017). TATHYA: A multi-classifier system for detecting check-worthy statements in political debates. In Proceedings of the 2017 ACM on conference on information and knowledge management, CIKM (pp. 2259\u20132262). ACM. https:\/\/doi.org\/10.1145\/3132847.3133150","DOI":"10.1145\/3132847.3133150"},{"key":"9692_CR191","doi-asserted-by":"publisher","unstructured":"Paul, D., Opitz, J., Becker, M., Kobbe, J., Hirst, G., & Frank, A. (2020). Argumentative relation classification with background knowledge. In Computational models of argument - proceedings of COMMA (vol. 326., pp. 319\u2013330). IOS Press. https:\/\/doi.org\/10.3233\/FAIA200515","DOI":"10.3233\/FAIA200515"},{"key":"9692_CR192","doi-asserted-by":"publisher","unstructured":"Pecune, F., & Marsella, S. (2020). A framework to co-optimize task and social dialogue policies using reinforcement learning. In IVA \u201920: ACM international conference on intelligent virtual agents (pp. 45:1\u201345:8). ACM. https:\/\/doi.org\/10.1145\/3383652.3423877","DOI":"10.1145\/3383652.3423877"},{"key":"9692_CR193","doi-asserted-by":"publisher","unstructured":"Peldszus, A. (2014). Towards segment-based recognition of argumentation structure in short texts. In Proceedings of the first workshop on argument mining, ArgMining@ACL (pp. 88\u201397). The Association for Computer Linguistics.https:\/\/doi.org\/10.3115\/v1\/w14-2112","DOI":"10.3115\/v1\/w14-2112"},{"issue":"1","key":"9692_CR194","doi-asserted-by":"publisher","first-page":"1","DOI":"10.4018\/jcini.2013010101","volume":"7","author":"A Peldszus","year":"2013","unstructured":"Peldszus, A., & Stede, M. (2013). From argument diagrams to argumentation mining in texts: A survey. International Journal of Cognitive Informatics and Natural Intelligence, 7(1), 1\u201331. https:\/\/doi.org\/10.4018\/jcini.2013010101","journal-title":"International Journal of Cognitive Informatics and Natural Intelligence"},{"key":"9692_CR195","doi-asserted-by":"publisher","unstructured":"Peldszus, A., & Stede, M. (2015). Joint prediction in mst-style discourse parsing for argumentation mining. In Proceedings of the 2015 conference on empirical methods in natural language processing, EMNLP (pp. 938\u2013948). The Association for Computational Linguistics. https:\/\/doi.org\/10.18653\/v1\/d15-1110","DOI":"10.18653\/v1\/d15-1110"},{"key":"9692_CR196","doi-asserted-by":"publisher","unstructured":"Persing, I., & Ng, V. (2015). Modeling argument strength in student essays. In Proceedings of the 53rd annual meeting of the association for computational linguistics ACL (pp 543\u2013552). The Association for Computer Linguistics. https:\/\/doi.org\/10.3115\/v1\/p15-1053","DOI":"10.3115\/v1\/p15-1053"},{"key":"9692_CR197","doi-asserted-by":"publisher","unstructured":"Persing, I., & Ng, V. (2016). End-to-end argumentation mining in student essays. In NAACL HLT, the 2016 conference of the North American chapter of the association for computational linguistics: Human language technologies (pp. 1384\u20131394) The Association for Computational Linguistics. https:\/\/doi.org\/10.18653\/v1\/n16-1164","DOI":"10.18653\/v1\/n16-1164"},{"issue":"5\u20136","key":"9692_CR198","doi-asserted-by":"publisher","first-page":"601","DOI":"10.1016\/0378-2166(88)90050-1","volume":"12","author":"L Polanyi","year":"1988","unstructured":"Polanyi, L. (1988). A formal model of the structure of discourse. Journal of Pragmatics, 12(5\u20136), 601\u2013638.","journal-title":"Journal of Pragmatics"},{"key":"9692_CR199","doi-asserted-by":"publisher","first-page":"487","DOI":"10.1016\/j.ijar.2017.11.009","volume":"93","author":"S Polberg","year":"2018","unstructured":"Polberg, S., & Hunter, A. (2018). Empirical evaluation of abstract argumentation: Supporting the need for bipolar and probabilistic approaches. International Journal of Approximate Reasoning, 93, 487\u2013543. https:\/\/doi.org\/10.1016\/j.ijar.2017.11.009","journal-title":"International Journal of Approximate Reasoning"},{"key":"9692_CR200","doi-asserted-by":"publisher","unstructured":"Potyka, N. (2020). Abstract argumentation with markov networks. In ECAI - 24th European conference on artificial intelligence (vol. 325, pp 865\u2013872). IOS Press, https:\/\/doi.org\/10.3233\/FAIA200177","DOI":"10.3233\/FAIA200177"},{"key":"9692_CR201","doi-asserted-by":"crossref","unstructured":"Prakken, H. (2000). On dialogue systems with speech acts, arguments, and counterarguments. In European workshop on logics in artificial intelligence (pp. 224\u2013238). Springer.","DOI":"10.1007\/3-540-40006-0_16"},{"issue":"3","key":"9692_CR202","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1007\/s10503-005-4418-7","volume":"19","author":"H Prakken","year":"2005","unstructured":"Prakken, H. (2005). Ai & law, logic and argument schemes. Argumentation, 19(3), 303\u2013320.","journal-title":"Argumentation"},{"key":"9692_CR203","doi-asserted-by":"crossref","unstructured":"Prakken, H. (2005b). A study of accrual of arguments, with applications to evidential reasoning. In Proceedings of the 10th international conference on Artificial intelligence and law (pp. 85\u201394).","DOI":"10.1145\/1165485.1165500"},{"issue":"2","key":"9692_CR204","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1017\/S0269888906000865","volume":"21","author":"H Prakken","year":"2006","unstructured":"Prakken, H. (2006). Formal systems for persuasion dialogue. The Knowledge Engineering Review, 21(2), 163\u2013188. https:\/\/doi.org\/10.1017\/S0269888906000865","journal-title":"The Knowledge Engineering Review"},{"issue":"2","key":"9692_CR205","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1080\/19462160903564592","volume":"1","author":"H Prakken","year":"2010","unstructured":"Prakken, H. (2010). An abstract framework for argumentation with structured arguments. Argument & Computation, 1(2), 93\u2013124. https:\/\/doi.org\/10.1080\/19462160903564592","journal-title":"Argument & Computation"},{"key":"9692_CR206","unstructured":"Prakken, H. (2017). Historical overview of formal argumentation. FLAP 4(8). http:\/\/www.collegepublications.co.uk\/downloads\/ifcolog00017.pdf"},{"key":"9692_CR207","doi-asserted-by":"crossref","unstructured":"Prakken, H. (2019). Modelling accrual of arguments in aspic+. In Proceedings of the seventeenth international conference on artificial intelligence and law (pp. 103\u2013112).","DOI":"10.1145\/3322640.3326703"},{"key":"9692_CR208","doi-asserted-by":"crossref","unstructured":"Prakken, H., & Sartor, G. (2002). The role of logic in computational models of legal argument: A critical survey. In Computational logic: Logic programming and beyond (pp. 342\u2013381).","DOI":"10.1007\/3-540-45632-5_14"},{"key":"9692_CR209","doi-asserted-by":"publisher","first-page":"214","DOI":"10.1016\/j.artint.2015.06.005","volume":"227","author":"H Prakken","year":"2015","unstructured":"Prakken, H., & Sartor, G. (2015). Law and logic: A review from an argumentation perspective. Artificial Intelligence, 227, 214\u2013245. https:\/\/doi.org\/10.1016\/j.artint.2015.06.005","journal-title":"Artificial Intelligence"},{"key":"9692_CR210","doi-asserted-by":"crossref","unstructured":"Prakken, H., & Vreeswijk, G. (2001). Logics for defeasible argumentation. In Handbook of philosophical logic (pp. 219\u2013318). Springer.","DOI":"10.1007\/978-94-017-0456-4_3"},{"key":"9692_CR211","doi-asserted-by":"publisher","unstructured":"Rach, N., Weber, K., Pragst, L., Andr\u00e9, E., Minker, W., & Ultes, S. (2018). EVA: A multimodal argumentative dialogue system. In Proceedings of the 2018 on international conference on multimodal interaction, ICMI (pp 551\u2013552) ACMhttps:\/\/doi.org\/10.1145\/3242969.3266292","DOI":"10.1145\/3242969.3266292"},{"key":"9692_CR212","unstructured":"Rach, N., Matsuda, Y., Daxenberger, J., Ultes, S., Yasumoto, K., & Minker, W. (2020). Evaluation of argument search approaches in the context of argumentative dialogue systems. In Proceedings of The 12th language resources and evaluation conference, LREC. European language resources association (pp. 513\u2013522). https:\/\/aclanthology.org\/2020.lrec-1.65\/"},{"key":"9692_CR213","doi-asserted-by":"crossref","unstructured":"Rago, A., & Toni, F. (2017). Quantitative argumentation debates with votes for opinion polling. In PRIMA 2017: Principles and practice of multi-agent systems: 20th international conference (pp. 369\u2013385) Nice, France, October 30\u2013November 3, 2017, Proceedings 20, Springer.","DOI":"10.1007\/978-3-319-69131-2_22"},{"key":"9692_CR214","unstructured":"Rago, A., Toni, F., Aurisicchio, M., & Baroni, P. (2016). Discontinuity-free decision support with quantitative argumentation debates. In Principles of knowledge representation and reasoning: proceedings of the 15th international conference, KR. (pp. 63\u201373) AAAI Press. http:\/\/www.aaai.org\/ocs\/index.php\/KR\/KR16\/paper\/view\/12874"},{"issue":"4","key":"9692_CR215","doi-asserted-by":"publisher","first-page":"343","DOI":"10.1017\/S0269888904000098","volume":"18","author":"I Rahwan","year":"2003","unstructured":"Rahwan, I., Ramchurn, S.D., Jennings, N.R., McBurney, P., Parsons, S., & Sonenberg, L.\u00a0(2003). Argumentation-based negotiation. The Knowledge Engineering Review, 18(4), 343\u2013375.","journal-title":"The Knowledge Engineering Review"},{"issue":"8","key":"9692_CR216","doi-asserted-by":"publisher","first-page":"1483","DOI":"10.1111\/j.1551-6709.2010.01123.x","volume":"34","author":"I Rahwan","year":"2010","unstructured":"Rahwan, I., Madakkatel, M.I., Bonnefon, J.F., Awan, R.N., & Abdallah, S. (2010). Behavioral experiments for assessing the abstract argumentation semantics of reinstatement. Cognitive Science, 34(8), 1483\u20131502. https:\/\/doi.org\/10.1111\/j.1551-6709.2010.01123.x","journal-title":"Cognitive Science"},{"key":"9692_CR217","doi-asserted-by":"crossref","unstructured":"Reed, C. (1998). Dialogue frames in agent communication. In Proceedings international conference on multi agent systems (Cat. No. 98EX160) (pp. 246\u2013253) IEEE.","DOI":"10.1109\/ICMAS.1998.699056"},{"key":"9692_CR218","unstructured":"Reed, C., & Long, D. (1997). Content ordering in the generation of persuasive discourse. In Proceedings of the 15th international joint conference on artificial intelligence IJCAI (pp. 1022\u20131029). Morgan Kaufmann. http:\/\/ijcai.org\/Proceedings\/97-2\/Papers\/034.pdf"},{"key":"9692_CR219","doi-asserted-by":"crossref","unstructured":"Reed, C., Long, D., & Fox, M. (1996). An architecture for argumentative dialogue planning. In International conference on formal and applied practical reasoning (pp. 555\u2013566). Springer.","DOI":"10.1007\/3-540-61313-7_100"},{"issue":"1","key":"9692_CR220","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1017\/S0269888907001051","volume":"22","author":"C Reed","year":"2007","unstructured":"Reed, C., Walton, D., & Macagno, F. (2007). Argument diagramming in logic, law and artificial intelligence. The Knowledge Engineering Review, 22(1), 87\u2013109.","journal-title":"The Knowledge Engineering Review"},{"key":"9692_CR221","doi-asserted-by":"publisher","unstructured":"Reisert, P., Inoue, N., Okazaki, N., & Inui, K. (2015). A computational approach for generating toulmin model argumentation. In Proceedings of the 2nd workshop on argumentation mining, ArgMining@HLT-NAACL (pp. 45\u201355). The Association for Computational Linguistics. https:\/\/doi.org\/10.3115\/v1\/w15-0507","DOI":"10.3115\/v1\/w15-0507"},{"key":"9692_CR222","doi-asserted-by":"crossref","unstructured":"Reynolds, R. A., & Reynolds, J. L. (2002). What we know so far about evidence. The persuasion handbook: Developments in theory and practice (pp. 427\u2013432).","DOI":"10.4135\/9781412976046.n22"},{"key":"9692_CR223","doi-asserted-by":"publisher","unstructured":"Rinott, R., Dankin, L., Alzate, C., Khapra, M.M., Aharoni, E., & Slonim, N. (2015). Show me your evidence - an automatic method for context dependent evidence detection. In Proceedings of the 2015 conference on empirical methods in natural language processing, EMNLP (pp. 440\u2013450). The Association for Computational Linguistics. https:\/\/doi.org\/10.18653\/v1\/d15-1050","DOI":"10.18653\/v1\/d15-1050"},{"key":"9692_CR224","doi-asserted-by":"publisher","unstructured":"Rocha, G., Stab, C., Cardoso, H.L., & Gurevych, I. (2018). Cross-lingual argumentative relation identification: From English to Portuguese. In Proceedings of the 5th workshop on argument mining, ArgMining@EMNLP 2018 (pp. 144\u2013154) Brussels, Belgium, November 1, 2018. Association for Computational Linguistics. https:\/\/doi.org\/10.18653\/v1\/w18-5217","DOI":"10.18653\/v1\/w18-5217"},{"issue":"4","key":"9692_CR225","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2983925","volume":"6","author":"A Rosenfeld","year":"2016","unstructured":"Rosenfeld, A., & Kraus, S. (2016). Providing arguments in discussions on the basis of the prediction of human argumentative behavior. ACM Transactions on Interactive Intelligent Systems, 6(4), 1\u201330. https:\/\/doi.org\/10.1145\/2983925","journal-title":"ACM Transactions on Interactive Intelligent Systems"},{"key":"9692_CR226","doi-asserted-by":"publisher","unstructured":"Rosenfeld, A., & Kraus, S. (2016b). Strategical argumentative agent for human persuasion. In ECAI 2016 - 22nd European conference on artificial intelligence (vol. 285, pp. 320\u2013328). IOS Press. https:\/\/doi.org\/10.3233\/978-1-61499-672-9-320","DOI":"10.3233\/978-1-61499-672-9-320"},{"issue":"1","key":"9692_CR227","doi-asserted-by":"publisher","first-page":"68","DOI":"10.4102\/sajip.v29i1.88","volume":"29","author":"S Rothmann","year":"2003","unstructured":"Rothmann, S., & Coetzer, E. P. (2003). The big five personality dimensions and job performance. SA Journal of Industrial Psychology, 29(1), 68\u201374.","journal-title":"SA Journal of Industrial Psychology"},{"key":"9692_CR228","doi-asserted-by":"crossref","unstructured":"Ruiz-Dolz, R., & Lawrence, J. (2023). Detecting argumentative fallacies in the wild: Problems and limitations of large language models. In Proceedings of the 10th workshop on argument mining, association for computational linguistics.","DOI":"10.18653\/v1\/2023.argmining-1.1"},{"key":"9692_CR229","unstructured":"Ruiz-Dolz, R., Alemany, J., Heras, S., & Garc\u00eda-Fornes, A. (2019a). Automatic generation of explanations to prevent privacy violations. In Proceedings of the 2nd EXplainable AI in Law Workshop (XAILA 2019) (vol. 2681). CEUR-WS.org. http:\/\/ceur-ws.org\/Vol-2681\/xaila2019-paper3.pdf"},{"key":"9692_CR230","unstructured":"Ruiz-Dolz, R., Heras, S., Alemany, J., & Garc\u00eda-Fornes, A. (2019b). Towards an argumentation system for assisting users with privacy management in online social networks. In Proceedings of the 19th workshop on computational models of natural argument CMNA@PERSUASIVE 2019, vol 2346. CEUR-WS.org (pp. 17\u201328).http:\/\/ceur-ws.org\/Vol-2346\/paper2.pdf"},{"issue":"6","key":"9692_CR231","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1109\/MIS.2021.3073993","volume":"36","author":"R Ruiz-Dolz","year":"2021","unstructured":"Ruiz-Dolz, R., Alemany, J., Barber\u00e1, S.M.H., & Garc\u00eda-Fornes, A.\u00a0(2021). Transformer-based models for automatic identification of argument relations: A cross-domain evaluation. IEEE Intelligent Systems, 36(6), 62\u201370. https:\/\/doi.org\/10.1109\/MIS.2021.3073993","journal-title":"IEEE Intelligent Systems"},{"key":"9692_CR232","unstructured":"Ruiz-Dolz, R., Alemany, J., Heras, S., & Garc\u00eda-Fornes, A. (2021). On the prevention of privacy threats: How can we persuade our social network users? CoRR abs\/2104.10004. https:\/\/arxiv.org\/abs\/2104.10004"},{"key":"9692_CR233","doi-asserted-by":"publisher","unstructured":"Ruiz-Dolz, R., Taverner, J., Heras, S., Garcia-Fornes, A., & Botti, V. (2022). A qualitative analysis of the persuasive properties of argumentation schemes. In UMAP \u201922: 30th ACM conference on user modeling, adaptation and personalization (pp. 1\u201311). Barcelona, Spain, July 4 - 7, 2022. ACM. https:\/\/doi.org\/10.1145\/3503252.3531324","DOI":"10.1145\/3503252.3531324"},{"key":"9692_CR234","doi-asserted-by":"crossref","unstructured":"Ruiz-Dolz, R., Heras, S., & Garcia, A. (2023). Automatic debate evaluation with argumentation semantics and natural language argument graph networks. In Proceedings of the 2023 conference on empirical methods in natural language processing (pp. 6030\u20136040).","DOI":"10.18653\/v1\/2023.emnlp-main.368"},{"key":"9692_CR235","unstructured":"Ruiz-Dolz, R., Chen, C.C., Kando, N., & Chen, H.H. (2024a). Learning strategies for robust argument mining: An analysis of variations in language and domain. In Proceedings of the 2024 joint international conference on computational linguistics, language resources and evaluation (LREC-COLING 2024). (pp. 10286\u201310292)."},{"key":"9692_CR236","doi-asserted-by":"crossref","unstructured":"Ruiz-Dolz, R., Lawrence, J., Schad, E., & Reed, C. (2024b). Overview of dialam-2024: Argument mining in natural language dialogues. In Proceedings of the 11th workshop on argument mining (ArgMining 2024) (pp. 83\u201392).","DOI":"10.18653\/v1\/2024.argmining-1.8"},{"issue":"1","key":"9692_CR237","doi-asserted-by":"publisher","first-page":"229","DOI":"10.1007\/s11257-023-09370-1","volume":"34","author":"R Ruiz-Dolz","year":"2024","unstructured":"Ruiz-Dolz, R., Taverner, J., Heras Barber\u00e1, S.M., & Garc\u00eda-Fornes, A.\u00a0(2024). Persuasion-enhanced computational argumentative reasoning through argumentation-based persuasive frameworks. User Modeling and User-Adapted Interaction, 34(1), 229\u2013258.","journal-title":"User Modeling and User-Adapted Interaction"},{"key":"9692_CR238","doi-asserted-by":"publisher","DOI":"10.1016\/j.dib.2024.111087","volume":"57","author":"R Ruiz-Dolz","year":"2024","unstructured":"Ruiz-Dolz, R., Taverner, J., Lawrence, J., & Reed, C.\u00a0(2024). Nlas-multi: A multilingual corpus of automatically generated natural language argumentation schemes. Data in Brief, 57, 111087. https:\/\/doi.org\/10.1016\/j.dib.2024.111087","journal-title":"Data in Brief"},{"key":"9692_CR239","doi-asserted-by":"crossref","unstructured":"Saadat-Yazdi, A., Pan, J.Z., & K\u00f6kciyan, N. (2023). Uncovering implicit inferences for improved relational argument mining. In Proceedings of the 17th conference of the European chapter of the association for computational linguistics (pp. 2484\u20132495).","DOI":"10.18653\/v1\/2023.eacl-main.182"},{"key":"9692_CR240","unstructured":"Sacks, H., Schegloff, E.A., & Jefferson, G. (1978). A simplest systematics for the organization of turn taking for conversation. In Studies in the organization of conversational interaction (pp. 7\u201355). Elsevier."},{"key":"9692_CR241","doi-asserted-by":"crossref","unstructured":"Saha, S., & Srihari, R.K. (2024). Turiya at dialam-2024: Inference anchoring theory based llm parsers. In Proceedings of the 11th workshop on argument mining (ArgMining 2024) (pp. 124\u2013129).","DOI":"10.18653\/v1\/2024.argmining-1.13"},{"key":"9692_CR242","unstructured":"Saha, S., Das, S., & Srihari, R.K. (2022). Dialo-ap: A dependency parsing based argument parser for dialogues. In Proceedings of the 29th international conference on computational linguistics, COLING 2022 (pp. 887\u2013901). Gyeongju, Republic of Korea, October 12-17, 2022. International Committee on Computational Linguistics. https:\/\/aclanthology.org\/2022.coling-1.74"},{"issue":"2","key":"9692_CR243","doi-asserted-by":"publisher","first-page":"137","DOI":"10.3233\/AAC-180035","volume":"9","author":"P Saint-Dizier","year":"2018","unstructured":"Saint-Dizier, P. (2018). A two-level approach to generate synthetic argumentation reports. Argument & Computation, 9(2), 137\u2013154. https:\/\/doi.org\/10.3233\/AAC-180035","journal-title":"Argument & Computation"},{"key":"9692_CR244","doi-asserted-by":"publisher","unstructured":"Sardianos, C., Katakis, I.M., Petasis, G., & Karkaletsis, V. (2015). Argument extraction from news. In Proceedings of the 2nd workshop on argumentation mining, ArgMining@HLT-NAACL (pp. 56\u201366). The Association for Computational Linguistics. https:\/\/doi.org\/10.3115\/v1\/w15-0508","DOI":"10.3115\/v1\/w15-0508"},{"key":"9692_CR245","unstructured":"Sarkadi, S. (2024). Deception analysis with artificial intelligence: An interdisciplinary perspective. arXiv preprint arXiv:2406.05724"},{"key":"9692_CR246","doi-asserted-by":"publisher","unstructured":"Sato, M., Yanai, K., Miyoshi, T., Yanase, T., Iwayama, M., Sun, Q., & Niwa, Y. (2015). End-to-end argument generation system in debating. In Proceedings of the 53rd annual meeting of the association for computational linguistics ACL (pp. 109\u2013114). The Association for Computer Linguistics. https:\/\/doi.org\/10.3115\/v1\/p15-4019","DOI":"10.3115\/v1\/p15-4019"},{"key":"9692_CR247","doi-asserted-by":"publisher","unstructured":"Schiller, B., Daxenberger, J., & Gurevych, I. (2021). Aspect-controlled neural argument generation. In Proceedings of the 2021 conference of the North American chapter of the association for computational linguistics NAACL-HLT (pp. 380\u2013396). Association for Computational Linguistics. https:\/\/doi.org\/10.18653\/v1\/2021.naacl-main.34","DOI":"10.18653\/v1\/2021.naacl-main.34"},{"key":"9692_CR248","volume-title":"Lucius annaeus seneca de beneficiis libri VII","author":"LA Seneca","year":"1950","unstructured":"Seneca, L. A. (1950). Lucius annaeus seneca de beneficiis libri VII. University of California Press."},{"key":"9692_CR249","doi-asserted-by":"crossref","unstructured":"Shnarch, E., Alzate, C., Dankin, L., Gleize, M., Hou, Y., Choshen, L., Aharonov, R., & Slonim, N. (2018). Will it blend? blending weak and strong labeled data in a neural network for argumentation mining. In Proceedings of the 56th annual meeting of the association for computational linguistics, ACL 2018, Melbourne, Australia, July (pp. 15-20) 2018, volume 2: Short Papers. Association for Computational Linguistics. https:\/\/aclanthology.org\/P18-2095\/","DOI":"10.18653\/v1\/P18-2095"},{"key":"9692_CR250","doi-asserted-by":"crossref","unstructured":"Sierra, C., Jennings, N.R., Noriega, P., & Parsons, S. (1997). A framework for argumentation-based negotiation. In International workshop on agent theories, architectures, and languages (pp. 177\u2013192). Springer.","DOI":"10.1007\/BFb0026758"},{"issue":"2\u20133","key":"9692_CR251","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1016\/0004-3702(92)90069-A","volume":"53","author":"GR Simari","year":"1992","unstructured":"Simari, G. R., & Loui, R. P. (1992). A mathematical treatment of defeasible reasoning and its implementation. Artificial Intelligence, 53(2\u20133), 125\u2013157. https:\/\/doi.org\/10.1016\/0004-3702(92)90069-A","journal-title":"Artificial Intelligence"},{"issue":"7850","key":"9692_CR252","doi-asserted-by":"publisher","first-page":"379","DOI":"10.1038\/s41586-021-03215-w","volume":"591","author":"N Slonim","year":"2021","unstructured":"Slonim, N., Bilu, Y., Alzate, C., Bar-Haim, R., Bogin, B., Bonin, F., Choshen, L., Cohen-Karlik, E., Dankin, L., Edelstein, L., & Ein-Dor, L.\u00a0(2021). An autonomous debating system. Nature, 591(7850), 379\u2013384.","journal-title":"Nature"},{"key":"9692_CR253","doi-asserted-by":"publisher","unstructured":"Sousa, A., Leite, B., Rocha, G., & Lopes Cardoso, H. (2021). Cross-lingual annotation projection for argument mining in portuguese. In Progress in artificial intelligence - 20th EPIA conference on artificial intelligence EPIA 2021, Virtual Event, September 7-9, 2021, Proceedings, Lecture Notes in Computer Science (vol. 12981, pp. 752\u2013765). Springer. https:\/\/doi.org\/10.1007\/978-3-030-86230-5_59","DOI":"10.1007\/978-3-030-86230-5_59"},{"key":"9692_CR254","doi-asserted-by":"publisher","unstructured":"Stab, C., & Gurevych, I. (2014). Identifying argumentative discourse structures in persuasive essays. In Proceedings of the EMNLP. ACL (pp. 46\u201356). https:\/\/doi.org\/10.3115\/v1\/d14-1006","DOI":"10.3115\/v1\/d14-1006"},{"issue":"3","key":"9692_CR255","doi-asserted-by":"publisher","first-page":"619","DOI":"10.1162\/COLI_a_00295","volume":"43","author":"C Stab","year":"2017","unstructured":"Stab, C., & Gurevych, I. (2017). Parsing argumentation structures in persuasive essays. Computational Linguistics, 43(3), 619\u2013659. https:\/\/doi.org\/10.1162\/COLI_a_00295","journal-title":"Computational Linguistics"},{"key":"9692_CR256","doi-asserted-by":"publisher","unstructured":"Stab, C., Daxenberger, J., Stahlhut, C., Miller, T., Schiller, B., Tauchmann, C., Eger, S., & Gurevych, I. (2018a). Argumentext: Searching for arguments in heterogeneous sources. In Proceedings of the 2018 conference of the North American Chapter of the association for computational linguistics, NAACL-HLT (pp 21\u201325). Association for Computational Linguistics. https:\/\/doi.org\/10.18653\/v1\/n18-5005","DOI":"10.18653\/v1\/n18-5005"},{"key":"9692_CR257","doi-asserted-by":"crossref","unstructured":"Stab, C., Miller, T., & Gurevych, I. (2018b). Cross-topic argument mining from heterogeneous sources using attention-based neural networks. CoRR abs\/1802.05758. arxiv:1802.05758","DOI":"10.18653\/v1\/D18-1402"},{"key":"9692_CR258","doi-asserted-by":"publisher","unstructured":"Stede, M., & Schneider, J. (2018). Argumentation mining. Morgan & Claypool Publishers. https:\/\/doi.org\/10.2200\/S00883ED1V01Y201811HLT040","DOI":"10.2200\/S00883ED1V01Y201811HLT040"},{"key":"9692_CR259","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2021.103767","volume":"117","author":"N Stylianou","year":"2021","unstructured":"Stylianou, N., & Vlahavas, I. (2021). Transformed: End-to-end transformers for evidence-based medicine and argument mining in medical literature. Journal of Biomedical Informatics, 117, 103767.","journal-title":"Journal of Biomedical Informatics"},{"key":"9692_CR260","unstructured":"Subba, R., & Di\u00a0Eugenio, B. (2007). Automatic discourse segmentation using neural networks. In Proc. of the 11th workshop on the semantics and pragmatics of dialogue (pp. 189\u2013190)."},{"key":"9692_CR261","doi-asserted-by":"crossref","unstructured":"Sutton, R.S., & Barto, A.G. (1998). Reinforcement learning - an introduction. MIT Press. https:\/\/www.worldcat.org\/oclc\/37293240","DOI":"10.1109\/TNN.1998.712192"},{"key":"9692_CR262","doi-asserted-by":"publisher","unstructured":"Thimm, M. (2012). A probabilistic semantics for abstract argumentation. In ECAI 2012 - 20th European conference on artificial intelligence (vol. 242, pp. 750\u2013755). IOS Press. https:\/\/doi.org\/10.3233\/978-1-61499-098-7-750","DOI":"10.3233\/978-1-61499-098-7-750"},{"key":"9692_CR263","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1016\/j.artint.2017.08.006","volume":"252","author":"M Thimm","year":"2017","unstructured":"Thimm, M., & Villata, S. (2017). The first international competition on computational models of argumentation: Results and analysis. Artificial Intelligence, 252, 267\u2013294. https:\/\/doi.org\/10.1016\/j.artint.2017.08.006","journal-title":"Artificial Intelligence"},{"key":"9692_CR264","unstructured":"Thomas, R., Oren, N., & Masthoff, J. (2018). Argumessage: A system for automation of message generation using argumentation schemes. In Proceedings of the 18th workshop on computational models of argument (CMNA 2018)."},{"key":"9692_CR265","doi-asserted-by":"publisher","unstructured":"Thomas, R.J., Masthoff, J., & Oren, N. (2017). Adapting healthy eating messages to personality. In Persuasive technology - 12th international conference, PERSUASIVE, proceedings (vol. 10171, pp. 119\u2013132). Springer. https:\/\/doi.org\/10.1007\/978-3-319-55134-0_10","DOI":"10.1007\/978-3-319-55134-0_10"},{"key":"9692_CR266","doi-asserted-by":"publisher","first-page":"24","DOI":"10.3389\/frai.2019.00024","volume":"2","author":"RJ Thomas","year":"2019","unstructured":"Thomas, R. J., Masthoff, J., & Oren, N. (2019). Can I influence you? development of a scale to measure perceived persuasiveness and two studies showing the use of the scale. Frontiers in Artificial Intelligence, 2, 24. https:\/\/doi.org\/10.3389\/frai.2019.00024","journal-title":"Frontiers in Artificial Intelligence"},{"key":"9692_CR267","doi-asserted-by":"publisher","unstructured":"Thomas, R.J., Masthoff, J., & Oren, N. (2019b). Is argumessage effective? A critical evaluation of the persuasive message generation system. In Persuasive technology - 14th international conference PERSUASIVE, proceedings (vol. 11433, pp. 87\u201399). Springer. https:\/\/doi.org\/10.1007\/978-3-030-17287-9_8","DOI":"10.1007\/978-3-030-17287-9_8"},{"key":"9692_CR268","unstructured":"Thorburn, L., & Kruger, A. (2022). Optimizing language models for argumentative reasoning."},{"key":"9692_CR269","doi-asserted-by":"publisher","unstructured":"Toledo-Ronen, O., Orbach, M., Bilu, Y., Spector, A., & Slonim, N. (2020). Multilingual argument mining: Datasets and analysis. In Findings of the association for computational linguistics: EMNLP 2020, online event, 16-20 November 2020, findings of ACL, vol EMNLP 2020 (pp. 303\u2013317). Association for Computational Linguistics.https:\/\/doi.org\/10.18653\/v1\/2020.findings-emnlp.29","DOI":"10.18653\/v1\/2020.findings-emnlp.29"},{"issue":"1","key":"9692_CR270","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1080\/19462166.2013.869878","volume":"5","author":"F Toni","year":"2014","unstructured":"Toni, F. (2014). A tutorial on assumption-based argumentation. Argument & Computation, 5(1), 89\u2013117. https:\/\/doi.org\/10.1080\/19462166.2013.869878","journal-title":"Argument & Computation"},{"key":"9692_CR271","doi-asserted-by":"crossref","unstructured":"Toulmin, S.E. (2006). Reasoning in theory and practice. In Arguing on the Toulmin model (pp. 25\u201329). Springer.","DOI":"10.1007\/978-1-4020-4938-5_2"},{"key":"9692_CR272","doi-asserted-by":"crossref","unstructured":"Van\u00a0Eemeren, F.H., Grootendorst, R., & Grootendorst, R. (2004). A systematic theory of argumentation: The pragma-dialectical approach. Cambridge University Press.","DOI":"10.1017\/CBO9780511616389"},{"key":"9692_CR273","doi-asserted-by":"crossref","unstructured":"Van Eemeren, F.H., Grootendorst, R., Johnson, R.H., Plantin, C., & Willard, C.A. (2013). Fundamentals of argumentation theory: A handbook of historical backgrounds and contemporary developments. Routledge.","DOI":"10.4324\/9780203811306"},{"key":"9692_CR274","first-page":"357","volume":"96","author":"B Verheij","year":"1996","unstructured":"Verheij, B. (1996). Two approaches to dialectical argumentation: Admissible sets and argumentation stages. Proceedings NAIC, 96, 357\u2013368.","journal-title":"Proceedings NAIC"},{"issue":"3","key":"9692_CR275","doi-asserted-by":"publisher","first-page":"62","DOI":"10.4018\/jcini.2012070104","volume":"6","author":"MPG Villalba","year":"2012","unstructured":"Villalba, M. P. G., & Saint-Dizier, P. (2012). A framework to extract arguments in opinion texts. International Journal of Cognitive Informatics and Natural Intelligence, 6(3), 62\u201387. https:\/\/doi.org\/10.4018\/jcini.2012070104","journal-title":"International Journal of Cognitive Informatics and Natural Intelligence"},{"key":"9692_CR276","doi-asserted-by":"publisher","unstructured":"Visser, J., Lawrence, J., Wagemans, J., & Reed, C. (2018). Revisiting computational models of argument schemes: Classification, annotation, comparison. In Computational models of argument - proceedings of COMMA (vol. 305, pp. 313\u2013324) IOS Press.https:\/\/doi.org\/10.3233\/978-1-61499-906-5-313","DOI":"10.3233\/978-1-61499-906-5-313"},{"key":"9692_CR277","doi-asserted-by":"crossref","unstructured":"Visser, J., Lawrence, J., Reed, C., Wagemans, J., & Walton, D. (2020). Annotating argument schemes. In Argumentation through languages and cultures (pp. 101\u2013139). Springer.","DOI":"10.1007\/978-3-031-19321-7_6"},{"key":"9692_CR278","doi-asserted-by":"publisher","unstructured":"Wachsmuth, H., Naderi, N., Hou, Y., Bilu, Y., Prabhakaran, V., Thijm, T.A., Hirst, G., & Stein, B. (2017a). Computational argumentation quality assessment in natural language. In Proceedings of the 15th conference of the european chapter of the association for computational linguistics, EACL (pp. 176\u2013187). Association for Computational Linguistics. https:\/\/doi.org\/10.18653\/v1\/e17-1017","DOI":"10.18653\/v1\/e17-1017"},{"key":"9692_CR279","doi-asserted-by":"publisher","unstructured":"Wachsmuth, H., Potthast, M., Al Khatib, K., Ajjour, Y., Puschmann, J., Qu, J., Dorsch, J., Morari, V., Bevendorff, J., & Stein, B. (2017b). Building an argument search engine for the web. In Proceedings of the 4th workshop on argument mining, ArgMining@EMNLP (pp. 49\u201359). Association for Computational Linguistics. https:\/\/doi.org\/10.18653\/v1\/w17-5106","DOI":"10.18653\/v1\/w17-5106"},{"key":"9692_CR280","unstructured":"Wachsmuth, H., Stede, M., El Baff, R., Al Khatib, K., Skeppstedt, M., & Stein, B. (2018). Argumentation synthesis following rhetorical strategies. In Proceedings of the 27th international conference on computational linguistics, COLING (pp. 3753\u20133765). Association for Computational Linguistics. https:\/\/aclanthology.org\/C18-1318\/"},{"key":"9692_CR281","doi-asserted-by":"publisher","unstructured":"Walker, V., Foerster, D., Ponce, J.M., & Rosen, M. (2018). Evidence types, credibility factors, and patterns or soft rules for weighing conflicting evidence: Argument mining in the context of legal rules governing evidence assessment. In Proceedings of the 5th workshop on argument mining, ArgMining@EMNLP (pp. 68\u201378). Association for Computational Linguistics https:\/\/doi.org\/10.18653\/v1\/w18-5209","DOI":"10.18653\/v1\/w18-5209"},{"key":"9692_CR282","doi-asserted-by":"publisher","unstructured":"Walton, D. (2009). Argumentation theory: A very short introduction. In Argumentation in artificial intelligence (pp. 1\u201322). Springer https:\/\/doi.org\/10.1007\/978-0-387-98197-0_1","DOI":"10.1007\/978-0-387-98197-0_1"},{"key":"9692_CR283","unstructured":"Walton, D. (2019). Argumentation schemes and their application to argument mining. In J. A. Blair (Ed.), Studies in critical thinking, windsor studies in argumentation. (vol. 8, pp. 177\u2013211)."},{"issue":"1","key":"9692_CR284","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1075\/pc.20.1.01wal","volume":"20","author":"D Walton","year":"2012","unstructured":"Walton, D., & Gordon, T. F. (2012). The carneades model of argument invention. Pragmatics & Cognition, 20(1), 1\u201331.","journal-title":"Pragmatics & Cognition"},{"issue":"3","key":"9692_CR285","doi-asserted-by":"publisher","first-page":"219","DOI":"10.1080\/19462166.2015.1123772","volume":"6","author":"D Walton","year":"2015","unstructured":"Walton, D., & Macagno, F. (2015). A classification system for argumentation schemes. Argument & Computation, 6(3), 219\u2013245. https:\/\/doi.org\/10.1080\/19462166.2015.1123772","journal-title":"Argument & Computation"},{"key":"9692_CR286","doi-asserted-by":"crossref","unstructured":"Walton, D., Reed, C., & Macagno, F. (2008). Argumentation schemes. Cambridge University Press. http:\/\/www.cambridge.org\/us\/academic\/subjects\/philosophy\/logic\/argumentation-schemes","DOI":"10.1017\/CBO9780511802034"},{"key":"9692_CR287","doi-asserted-by":"crossref","unstructured":"Walton, D., & Atkinson, K. (2010). Argumentation in the framework of deliberation dialogue. In Arguing global governance (pp. 230\u2013250). Routledge .","DOI":"10.4324\/9780203842577-22"},{"issue":"2","key":"9692_CR288","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1353\/par.2001.0010","volume":"34","author":"DN Walton","year":"2001","unstructured":"Walton, D. N. (2001). Enthymemes, common knowledge, and plausible inference. Philosophy & rhetoric, 34(2), 93\u2013112.","journal-title":"Philosophy & rhetoric"},{"key":"9692_CR289","volume-title":"Commitment in dialogue: Basic concepts of interpersonal reasoning","author":"DN Walton","year":"1995","unstructured":"Walton, D. N., & Krabbe, E. C. W. (1995). Commitment in dialogue: Basic concepts of interpersonal reasoning. State University of New York Press."},{"key":"9692_CR290","doi-asserted-by":"publisher","first-page":"219","DOI":"10.1162\/tacl_a_00057","volume":"5","author":"L Wang","year":"2017","unstructured":"Wang, L., Beauchamp, N., Shugars, S., & Qin, K.\u00a0(2017). Winning on the merits: The joint effects of content and style on debate outcomes. Transactions of the Association for Computational Linguistics, 5, 219\u2013232.","journal-title":"Transactions of the Association for Computational Linguistics"},{"key":"9692_CR291","unstructured":"Waterschoot, C., van\u00a0den Hemel, E., & van\u00a0den Bosch, A. (2022). Detecting minority arguments for mutual understanding: A moderation tool for the online climate change debate. In Proceedings of the 29th international conference on computational linguistics, COLING 2022 (pp. 6715\u20136725) Gyeongju, Republic of Korea, October 12-17, 2022. International Committee on Computational Linguistics. https:\/\/aclanthology.org\/2022.coling-1.583"},{"key":"9692_CR292","doi-asserted-by":"crossref","unstructured":"Xydis, A., Hampson, C., Modgil, S., & Black, E. (2021). Towards a sound and complete dialogue system for handling enthymemes. In Logic and argumentation: 4th international conference, Proceedings 4 (pp. 437\u2013456). CLAR 2021, Hangzhou, China, October 20\u201322, 2021. Springer.","DOI":"10.1007\/978-3-030-89391-0_24"},{"key":"9692_CR293","doi-asserted-by":"publisher","unstructured":"Zhang, J., Kumar, R., Ravi, S., & Danescu-Niculescu-Mizil, C. (2016). Conversational flow in oxford-style debates. In NAACL HLT, The 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. The Association for Computational Linguistics (pp. 136\u2013141). https:\/\/doi.org\/10.18653\/v1\/n16-1017","DOI":"10.18653\/v1\/n16-1017"},{"key":"9692_CR294","unstructured":"Zukerman, I., McConachy, R., & Korb, K.B. (1998). Bayesian reasoning in an abductive mechanism for argument generation and analysis. In Proceedings of the 15th national conference on artificial intelligence AAAI (pp. 833\u2013838). AAAI Press \/ The MIT Press. http:\/\/www.aaai.org\/Library\/AAAI\/1998\/aaai98-118.php"},{"key":"9692_CR295","doi-asserted-by":"crossref","unstructured":"Zukerman, I., McConachy, R., & George, S. (2000). Using argumentation strategies in automated argument generation. In INLG 2000 - proceedings of the first international natural language generation conference (pp. 55\u201362). The Association for Computer Linguistics. https:\/\/aclanthology.org\/W00-1408\/","DOI":"10.3115\/1118253.1118262"}],"container-title":["Autonomous Agents and Multi-Agent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10458-025-09692-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10458-025-09692-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10458-025-09692-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,7]],"date-time":"2025-07-07T03:53:49Z","timestamp":1751860429000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10458-025-09692-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2,13]]},"references-count":295,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2025,6]]}},"alternative-id":["9692"],"URL":"https:\/\/doi.org\/10.1007\/s10458-025-09692-x","relation":{},"ISSN":["1387-2532","1573-7454"],"issn-type":[{"value":"1387-2532","type":"print"},{"value":"1573-7454","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,2,13]]},"assertion":[{"value":"28 January 2025","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 February 2025","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflic of interest"}}],"article-number":"11"}}