{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,18]],"date-time":"2026-07-18T05:03:38Z","timestamp":1784351018002,"version":"3.55.0"},"publisher-location":"Singapore","reference-count":20,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819233908","type":"print"},{"value":"9789819233915","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,7,19]],"date-time":"2026-07-19T00:00:00Z","timestamp":1784419200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,7,19]],"date-time":"2026-07-19T00:00:00Z","timestamp":1784419200000},"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":[[2027]]},"DOI":"10.1007\/978-981-92-3391-5_25","type":"book-chapter","created":{"date-parts":[[2026,7,18]],"date-time":"2026-07-18T04:42:51Z","timestamp":1784349771000},"page":"303-315","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Predictive Pruning for Graph of Thoughts in Multi-Hop Reasoning"],"prefix":"10.1007","author":[{"given":"Jiaren","family":"Zou","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Miao","family":"Fan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bo","family":"Gao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chen","family":"Ma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guanghui","family":"Shu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haoyi","family":"Xiong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,19]]},"reference":[{"key":"25_CR1","unstructured":"Abolhasani, M.S., Pan, R.: Leveraging LLM for automated ontology extraction and knowledge graph generation. arXiv preprint arXiv:2412.00608 (2024)"},{"key":"25_CR2","doi-asserted-by":"publisher","first-page":"1533","DOI":"10.18653\/v1\/D13-1160","volume-title":"Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing","author":"J Berant","year":"2013","unstructured":"Berant, J., Chou, A., Frostig, R., Liang, P.: Semantic parsing on freebase from question-answer Pairs. In: Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, pp. 1533\u20131544 (2013)"},{"key":"25_CR3","doi-asserted-by":"publisher","first-page":"1247","DOI":"10.1145\/1376616.1376746","volume-title":"Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data","author":"K Bollacker","year":"2008","unstructured":"Bollacker, K., Evans, C., Paritosh, P., Sturge, T., Taylor, J.: Freebase: a collaboratively created graph database for structuring human knowledge. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 1247\u20131250 (2008)"},{"key":"25_CR4","first-page":"1877","volume-title":"Advances in Neural Information Processing Systems","author":"T Brown","year":"2020","unstructured":"Brown, T., et al.: Language models are few-shot learners. In: Advances in Neural Information Processing Systems, vol. 33, pp. 1877\u20131901 (2020)"},{"key":"25_CR5","doi-asserted-by":"publisher","first-page":"3477","DOI":"10.1145\/3442381.3449992","volume-title":"Proceedings of the Web Conference 2021","author":"Y Gu","year":"2021","unstructured":"Gu, Y., et al.: Beyond IID: three levels of generalization for question answering on knowledge bases. In: Proceedings of the Web Conference 2021, pp. 3477\u20133488 (2021)"},{"key":"25_CR6","first-page":"1403","volume-title":"Proceedings of the 31st International Conference on Computational Linguistics","author":"C Huang","year":"2025","unstructured":"Huang, C., et al.: Embedding-informed adaptive retrieval-augmented generation of large language models. In: Proceedings of the 31st International Conference on Computational Linguistics, pp. 1403\u20131412 (2025)"},{"key":"25_CR7","first-page":"17682","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence.","author":"M Besta","year":"2024","unstructured":"Besta, M., et al.: Graph of thoughts: solving elaborate problems with large language models. In: Proceedings of the AAAI Conference on Artificial Intelligence., vol. 38(16), pp. 17682\u201317690 (2024)"},{"issue":"2","key":"25_CR8","doi-asserted-by":"publisher","first-page":"494","DOI":"10.1109\/TNNLS.2021.3070843","volume":"33","author":"S Ji","year":"2021","unstructured":"Ji, S., Pan, S., Cambria, E., Marttinen, P., Yu, P.S.: A survey on knowledge graphs: representation, acquisition, and applications. IEEE Trans. Neural Networks Learn. Syst. 33(2), 494\u2013514 (2021)","journal-title":"IEEE Trans. Neural Networks Learn. Syst."},{"key":"25_CR9","doi-asserted-by":"publisher","first-page":"4246","DOI":"10.18653\/v1\/2022.emnlp-main.285","volume-title":"Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing","author":"A Kedia","year":"2022","unstructured":"Kedia, A., Zaidi, M.A., Lee, H.: FIE: building a global probability space by leveraging early fusion in encoder for open-domain question answering. In: Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pp. 4246\u20134260 (2022)"},{"key":"25_CR10","doi-asserted-by":"publisher","first-page":"9410","DOI":"10.18653\/v1\/2023.findings-emnlp.631","volume-title":"Findings of the Association for Computational Linguistics: EMNLP 2023","author":"J Kim","year":"2023","unstructured":"Kim, J., Kwon, Y., Jo, Y., Choi, E.: KG-GPT: a general framework for reasoning on knowledge graphs using large language models. In: Findings of the Association for Computational Linguistics: EMNLP 2023, pp. 9410\u20139421 (2023)"},{"key":"25_CR11","unstructured":"Luo, L., Li, Y.F., Haffari, G., Pan, S.: Reasoning on graphs: faithful and interpretable large language model reasoning. arXiv preprint arXiv:2310.01061 (2023)"},{"key":"25_CR12","first-page":"27730","volume-title":"Advances in Neural Information Processing Systems","author":"L Ouyang","year":"2022","unstructured":"Ouyang, L., et al.: Training language models to follow instructions with human feedback. In: Advances in Neural Information Processing Systems, vol. 35, pp. 27730\u201327744 (2022)"},{"issue":"7","key":"25_CR13","doi-asserted-by":"publisher","first-page":"3580","DOI":"10.1109\/TKDE.2024.3352100","volume":"36","author":"S Pan","year":"2024","unstructured":"Pan, S., Luo, L., Wang, Y., Chen, C., Wang, J., Wu, X.: Unifying large language models and knowledge graphs: a roadmap. IEEE Trans. Knowl. Data Eng. 36(7), 3580\u20133599 (2024)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"25_CR14","first-page":"641","volume-title":"Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies","author":"A Talmor","year":"2018","unstructured":"Talmor, A., Berant, J.: The web as a knowledge-base for answering complex questions. In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 641\u2013651 (2018)"},{"key":"25_CR15","unstructured":"Wang, X., et al.: Self-consistency improves chain of thought reasoning in language models. arXiv preprint arXiv:2203.11171 (2022)"},{"key":"25_CR16","first-page":"24824","volume-title":"Advances in Neural Information Processing Systems","author":"J Wei","year":"2022","unstructured":"Wei, J., et al.: Chain-of-thought prompting elicits reasoning in large language models. In: Advances in Neural Information Processing Systems, vol. 35, pp. 24824\u201324837 (2022)"},{"key":"25_CR17","first-page":"10370","volume-title":"Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics","author":"Y Wen","year":"2024","unstructured":"Wen, Y., Wang, Z., Sun, J.: MindMap: knowledge graph prompting sparks graph of thoughts in large language models. In: Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics, pp. 10370\u201310388 (2024)"},{"key":"25_CR18","unstructured":"Xu, M., Chen, K., Bai, X., Yang, M., Zhao, T., Zhang, M.: LLM-based discriminative reasoning for knowledge graph question answering. arXiv preprint arXiv:2412.12643 (2024)"},{"key":"25_CR19","unstructured":"Yao, S., et al.: Synergizing reasoning and acting in language models. arXiv preprint arXiv:2210.03629 (2022)"},{"key":"25_CR20","first-page":"11809","volume-title":"Advances in Neural Information Processing Systems","author":"S Yao","year":"2023","unstructured":"Yao, S., et al.: Tree of thoughts: deliberate problem solving with large language models. In: Advances in Neural Information Processing Systems, vol. 36, pp. 11809\u201311822 (2023)"}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing Technology and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-92-3391-5_25","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,18]],"date-time":"2026-07-18T04:42:56Z","timestamp":1784349776000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-92-3391-5_25"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,19]]},"ISBN":["9789819233908","9789819233915"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-981-92-3391-5_25","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,19]]},"assertion":[{"value":"19 July 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Toronto","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Canada","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2026","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 July 2026","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 July 2026","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2026a","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/2026\/index.htm","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}