{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,20]],"date-time":"2025-10-20T00:44:50Z","timestamp":1760921090202,"version":"build-2065373602"},"publisher-location":"Cham","reference-count":29,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032090430","type":"print"},{"value":"9783032090447","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,10,20]],"date-time":"2025-10-20T00:00:00Z","timestamp":1760918400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,10,20]],"date-time":"2025-10-20T00:00:00Z","timestamp":1760918400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-3-032-09044-7_2","type":"book-chapter","created":{"date-parts":[[2025,10,19]],"date-time":"2025-10-19T14:34:26Z","timestamp":1760884466000},"page":"16-27","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Rewarding Sentiment Consistency: Reinforcement Learning for\u00a0Multilingual Summarization"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-2581-8110","authenticated-orcid":false,"given":"Mikhail","family":"Krasitskii","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1307-1647","authenticated-orcid":false,"given":"Olga","family":"Kolesnikova","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7468-9603","authenticated-orcid":false,"given":"Liliana Chanona","family":"Hernandez","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3901-3522","authenticated-orcid":false,"given":"Grigori","family":"Sidorov","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7845-9039","authenticated-orcid":false,"given":"Alexander","family":"Gelbukh","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,10,20]]},"reference":[{"key":"2_CR1","first-page":"993","volume":"3","author":"DM Blei","year":"2003","unstructured":"Blei, D.M., et al.: Latent dirichlet allocation. J. Mach. Learn. Res. 3, 993\u20131022 (2003)","journal-title":"J. Mach. Learn. Res."},{"key":"2_CR2","unstructured":"Bra\u017einskas, A., et al.: Efficient controllable text generation. In: Proceedings of COLING (2020)"},{"key":"2_CR3","unstructured":"Cho, H., et al.: Rethinking reinforcement learning for natural language processing. In: Proceedings of AAAI (2022)"},{"key":"2_CR4","doi-asserted-by":"crossref","unstructured":"Conneau, A., et al.: Unsupervised cross-lingual representation learning at scale. In: Proceedings of ACL 2020, pp. 8440\u20138451. Association for Computational Linguistics (2020)","DOI":"10.18653\/v1\/2020.acl-main.747"},{"issue":"1","key":"2_CR5","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1177\/001316446002000104","volume":"20","author":"J Cohen","year":"1960","unstructured":"Cohen, J.: A coefficient of agreement for nominal scales. Educ. Psychol. Measur. 20(1), 37\u201346 (1960)","journal-title":"Educ. Psychol. Measur."},{"issue":"1","key":"2_CR6","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10462-016-9475-9","volume":"47","author":"M Gambhir","year":"2017","unstructured":"Gambhir, M., Gupta, V.: Recent automatic text summarization techniques. Artif. Intell. Rev. 47(1), 1\u201366 (2017)","journal-title":"Artif. Intell. Rev."},{"key":"2_CR7","unstructured":"Gao, Y., et al.: Tonal language processing in neural networks. In: ACL (2023)"},{"issue":"2","key":"2_CR8","first-page":"1","volume":"56","author":"A Gelbukh","year":"2023","unstructured":"Gelbukh, A., Sidorov, G., Balouchzahi, F.: Recent advances in multilingual text summarization: a comprehensive survey. ACM Comput. Surv. 56(2), 1\u201335 (2023)","journal-title":"ACM Comput. Surv."},{"key":"2_CR9","volume":"10","author":"LC Hernandez","year":"2023","unstructured":"Hernandez, L.C., Sidorov, G.: Hope speech detection in social media: challenges and opportunities. JMIR Mental Health 10, e12345 (2023)","journal-title":"JMIR Mental Health"},{"key":"2_CR10","unstructured":"Hofstede, G., et al.: Cultures and organizations: software of the mind. McGraw-Hill (2010)"},{"key":"2_CR11","unstructured":"Keskar, N.S., et al.: CTRL: A conditional transformer language model for controllable generation. arXiv preprint arXiv:1909.05858 (2019)"},{"key":"2_CR12","unstructured":"Kolesnikova, O., Krasitskii, M., Ahmed, S.: Advancing sentiment preservation in code-mixed text summarization. In: Proceedings of the 14th International Conference on Natural Language Processing (ICON), pp. 221\u2013227 (2023)"},{"issue":"3","key":"2_CR13","first-page":"512","volume":"49","author":"M Krasitskii","year":"2023","unstructured":"Krasitskii, M., Kolesnikova, O.: Comparative analysis of sentiment preservation in multilingual text summarization. Comput. Linguist. 49(3), 512\u2013528 (2023)","journal-title":"Comput. Linguist."},{"key":"2_CR14","first-page":"111","volume":"61","author":"M Krasitskii","year":"2023","unstructured":"Krasitskii, M., Kolesnikova, O., Hernandez, L.C.: Multilingual analysis of sentiment distortion in abstractive summarization. ACL 61, 111\u2013123 (2023)","journal-title":"ACL"},{"key":"2_CR15","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1162\/tacl_a_00447","volume":"10","author":"J Kreutzer","year":"2022","unstructured":"Kreutzer, J., et al.: Quality at a glance: an audit of web-crawled multilingual datasets. Trans. Assoc. Comput. Linguist. 10, 50\u201372 (2022)","journal-title":"Trans. Assoc. Comput. Linguist."},{"key":"2_CR16","unstructured":"Lin, C.Y.: ROUGE: A package for automatic evaluation of summaries. In: Proceedings of the ACL Workshop on Text Summarization Branches Out, pp. 74\u201381. Association for Computational Linguistics (2004)"},{"key":"2_CR17","doi-asserted-by":"publisher","first-page":"726","DOI":"10.1162\/tacl_a_00343","volume":"8","author":"Y Liu","year":"2020","unstructured":"Liu, Y., et al.: Multilingual denoising pre-training for neural machine translation. Trans. Assoc. Comput. Linguist. 8, 726\u2013742 (2020)","journal-title":"Trans. Assoc. Comput. Linguist."},{"key":"2_CR18","unstructured":"Liu, Y., et al.: Efficient multilingual transformers for low-resource scenarios. Comput. Linguist. 48(2), (2022)"},{"key":"2_CR19","unstructured":"Nguyen, T., et al.: Efficient adapters for multilingual transformers. In: EMNLP (2021)"},{"key":"2_CR20","unstructured":"Paulus, R., et al.: A Deep Reinforced model for abstractive summarization. arXiv preprint arXiv:1705.04304 (2017)"},{"key":"2_CR21","doi-asserted-by":"crossref","unstructured":"Pfeiffer, J., et al.: Mad-X: An adapter-based framework for multi-task cross-lingual transfer. In: EMNLP (2020). https:\/\/aclanthology.org\/2020.emnlp-main.617\/","DOI":"10.18653\/v1\/2020.emnlp-main.617"},{"key":"2_CR22","unstructured":"Ranzato, M.A., et al.: Sequence level training with recurrent neural networks. In: Proceedings of ICLR (2015)"},{"key":"2_CR23","unstructured":"Scialom, T., et al.: Discriminative adversarial search for abstractive summarization. In: Proceedings of ICML (2020)"},{"key":"2_CR24","doi-asserted-by":"crossref","unstructured":"See, A., et al.: Get to the Point: Summarization with pointer-generator networks. In: Proceedings of ACL (2017)","DOI":"10.18653\/v1\/P17-1099"},{"key":"2_CR25","volume":"215","author":"G Sidorov","year":"2023","unstructured":"Sidorov, G., Balouchzahi, F., Gelbukh, A.: Hybrid approaches for improved sentiment retention in text summarization. Expert Syst. Appl. 215, 119078 (2023)","journal-title":"Expert Syst. Appl."},{"key":"2_CR26","unstructured":"Schulman, J., et al.: Proximal policy optimization algorithms. arXiv preprint arXiv:1707.06347 (2017)"},{"key":"2_CR27","doi-asserted-by":"crossref","unstructured":"Tang, D., et al.: Aspect level sentiment classification with deep memory network. In: Proceedings of EMNLP (2016)","DOI":"10.18653\/v1\/D16-1021"},{"key":"2_CR28","doi-asserted-by":"crossref","unstructured":"Xue, L., et al.: mT5: A massively multilingual pre-trained text-to-text transformer. In: Proceedings of NAACL-HLT 2021, pp. 483\u2013498. Association for Computational Linguistics (2021)","DOI":"10.18653\/v1\/2021.naacl-main.41"},{"key":"2_CR29","unstructured":"Zhang, T., Kishore, V., Wu, F., Weinberger, K.Q., Artzi, Y.: BERTScore: Evaluating text generation with BERT. In: Proceedings of the International Conference on Learning Representations (2019)"}],"container-title":["Lecture Notes in Computer Science","Advances in Soft Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-09044-7_2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,19]],"date-time":"2025-10-19T14:34:30Z","timestamp":1760884470000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-09044-7_2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,20]]},"ISBN":["9783032090430","9783032090447"],"references-count":29,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-09044-7_2","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,20]]},"assertion":[{"value":"20 October 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors declare no competing interests","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"MICAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Mexican International Conference on Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Guanajuato","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Mexico","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 November 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 November 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"micai2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/micai.org\/2025\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}