{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T11:26:54Z","timestamp":1772537214999,"version":"3.50.1"},"reference-count":33,"publisher":"Elsevier BV","issue":"5","license":[{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["72074108"],"award-info":[{"award-number":["72074108"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008048","name":"Nanjing University","doi-asserted-by":"publisher","award":["010814370113"],"award-info":[{"award-number":["010814370113"]}],"id":[{"id":"10.13039\/501100008048","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["010814370338"],"award-info":[{"award-number":["010814370338"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Information Processing & Management"],"published-print":{"date-parts":[[2025,9]]},"DOI":"10.1016\/j.ipm.2025.104200","type":"journal-article","created":{"date-parts":[[2025,5,16]],"date-time":"2025-05-16T23:55:31Z","timestamp":1747439731000},"page":"104200","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":5,"title":["LOSDF: A logical optimization and semantic decoupling framework for question answering in multi-party conversations"],"prefix":"10.1016","volume":"62","author":[{"given":"Shu","family":"Zhou","sequence":"first","affiliation":[]},{"given":"Xin","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Jingwen","family":"Qiu","sequence":"additional","affiliation":[]},{"given":"Xiaomin","family":"Li","sequence":"additional","affiliation":[]},{"given":"Bin","family":"Shi","sequence":"additional","affiliation":[]},{"given":"Hao","family":"Wang","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.ipm.2025.104200_b1","first-page":"1","article-title":"DER-GCN: dialog and event relation-aware graph convolutional neural network for multimodal dialog emotion recognition","author":"Ai","year":"2024","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"key":"10.1016\/j.ipm.2025.104200_b2","series-title":"ICLR","article-title":"ELECTRA: Pre-training text encoders as discriminators rather than generators","author":"Clark","year":"2020"},{"key":"10.1016\/j.ipm.2025.104200_b3","doi-asserted-by":"crossref","unstructured":"Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2019). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In Proceedings of the 2019 conference of the North American chapter of the association for computational linguistics: human language technologies, volume 1 (long and short papers) (pp. 4171\u20134186).","DOI":"10.18653\/v1\/N19-1423"},{"key":"10.1016\/j.ipm.2025.104200_b4","series-title":"Proceedings of the 2023 conference on empirical methods in natural language processing","first-page":"7681","article-title":"MADNet: Maximizing addressee deduction expectation for multi-party conversation generation","author":"Gu","year":"2023"},{"key":"10.1016\/j.ipm.2025.104200_b5","doi-asserted-by":"crossref","unstructured":"Gu, J.-C., Tan, C.-H., Tao, C., Ling, Z.-H., Hu, H., Geng, X., & Jiang, D. (2022). HeterMPC: A Heterogeneous Graph Neural Network for Response Generation in Multi-Party Conversations. In Proceedings of the 60th annual meeting of the association for computational linguistics (volume 1: long papers) (pp. 5086\u20135097).","DOI":"10.18653\/v1\/2022.acl-long.349"},{"key":"10.1016\/j.ipm.2025.104200_b6","series-title":"ICASSP 2021-2021 IEEE international conference on acoustics, speech and signal processing","first-page":"7813","article-title":"Role aware multi-party dialogue question answering","author":"Hsu","year":"2021"},{"key":"10.1016\/j.ipm.2025.104200_b7","series-title":"MP2D: An automated topic shift dialogue generation framework leveraging knowledge graphs","author":"Hwang","year":"2024"},{"issue":"5","key":"10.1016\/j.ipm.2025.104200_b8","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2024.103803","article-title":"Integrating discourse features and response assessment for advancing empathetic dialogue","volume":"61","author":"Li","year":"2024","journal-title":"Information Processing & Management"},{"key":"10.1016\/j.ipm.2025.104200_b9","series-title":"Proceedings of the 28th international conference on computational linguistics","first-page":"2642","article-title":"Molweni: a challenge multiparty dialogues-based machine reading comprehension dataset with discourse structure","author":"Li","year":"2020"},{"key":"10.1016\/j.ipm.2025.104200_b10","series-title":"Proceedings of the eighth international joint conference on natural language processing (volume 1: long papers)","first-page":"986","article-title":"Dailydialog: A manually labelled multi-turn dialogue dataset","author":"Li","year":"2017"},{"issue":"1","key":"10.1016\/j.ipm.2025.104200_b11","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2023.103581","article-title":"Response generation in multi-modal dialogues with split pre-generation and cross-modal contrasting","volume":"61","author":"Li","year":"2024","journal-title":"Information Processing & Management"},{"key":"10.1016\/j.ipm.2025.104200_b12","series-title":"Self-and pseudo-self-supervised prediction of speaker and key-utterance for multi-party dialogue reading comprehension","author":"Li","year":"2021"},{"key":"10.1016\/j.ipm.2025.104200_b13","doi-asserted-by":"crossref","unstructured":"Li, Y., & Zhao, H. (2023a). EM Pre-training for Multi-party Dialogue Response Generation. In Proceedings of the 61st annual meeting of the association for computational linguistics (volume 1: long papers) (pp. 92\u2013103).","DOI":"10.18653\/v1\/2023.acl-long.7"},{"key":"10.1016\/j.ipm.2025.104200_b14","series-title":"Proceedings of the 61st annual meeting of the association for computational linguistics (volume 1: long papers)","first-page":"92","article-title":"EM pre-training for multi-party dialogue response generation","author":"Li","year":"2023"},{"key":"10.1016\/j.ipm.2025.104200_b15","series-title":"2023 international joint conference on neural networks","first-page":"1","article-title":"Coreference-aware double-channel attention network for multi-party dialogue reading comprehension","author":"Li","year":"2023"},{"key":"10.1016\/j.ipm.2025.104200_b16","series-title":"Findings of the association for computational linguistics: EMNLP 2023","first-page":"1817","article-title":"GLGR: Question-aware global-to-local graph reasoning for multi-party dialogue reading comprehension","author":"Li","year":"2023"},{"key":"10.1016\/j.ipm.2025.104200_b17","series-title":"Proceedings of the 2nd conference of the Asia-Pacific chapter of the association for computational linguistics and the 12th international joint conference on natural language processing (volume 1: long papers)","first-page":"148","article-title":"S+PAGE: A speaker and position-aware graph neural network model for emotion recognition in conversation","author":"Liang","year":"2022"},{"key":"10.1016\/j.ipm.2025.104200_b18","series-title":"Advancing large language models to capture varied speaking styles and respond properly in spoken conversations","author":"Lin","year":"2024"},{"key":"10.1016\/j.ipm.2025.104200_b19","first-page":"13433","article-title":"A graph reasoning network for multi-turn response selection via customized pre-training","volume":"vol. 35","author":"Liu","year":"2021"},{"key":"10.1016\/j.ipm.2025.104200_b20","first-page":"13406","article-title":"Filling the gap of utterance-aware and speaker-aware representation for multi-turn dialogue","volume":"vol. 35","author":"Liu","year":"2021"},{"key":"10.1016\/j.ipm.2025.104200_b21","doi-asserted-by":"crossref","first-page":"481","DOI":"10.1016\/j.future.2020.08.030","article-title":"A hybrid Chinese conversation model based on retrieval and generation","volume":"114","author":"Ma","year":"2021","journal-title":"Future Generation Computer Systems"},{"key":"10.1016\/j.ipm.2025.104200_b22","doi-asserted-by":"crossref","first-page":"2410","DOI":"10.1109\/TASLP.2023.3284516","article-title":"Enhanced speaker-aware multi-party multi-turn dialogue comprehension","volume":"31","author":"Ma","year":"2023","journal-title":"IEEE\/ACM Transactions on Audio, Speech, and Language Processing"},{"issue":"3","key":"10.1016\/j.ipm.2025.104200_b23","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2023.103635","article-title":"Dialogue acts enhanced extract\u2013abstract framework for meeting summarization","volume":"61","author":"Sun","year":"2024","journal-title":"Information Processing & Management"},{"key":"10.1016\/j.ipm.2025.104200_b24","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.inffus.2018.04.001","article-title":"Dynamic emotion modelling and anomaly detection in conversation based on emotional transition tensor","volume":"46","author":"Sun","year":"2019","journal-title":"Information Fusion"},{"key":"10.1016\/j.ipm.2025.104200_b25","series-title":"Proceedings of the 17th conference of the European chapter of the association for computational linguistics","first-page":"2696","article-title":"Do dialogue representations align with perception? an empirical study","author":"Wallbridge","year":"2023"},{"key":"10.1016\/j.ipm.2025.104200_b26","series-title":"Proceedings of the 20th annual sIGdial meeting on discourse and dialogue","first-page":"188","article-title":"FriendsQA: open-domain question answering on TV show transcripts","author":"Yang","year":"2019"},{"issue":"6","key":"10.1016\/j.ipm.2025.104200_b27","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2024.103824","article-title":"Situation-aware empathetic response generation","volume":"61","author":"Yang","year":"2024","journal-title":"Information Processing & Management"},{"key":"10.1016\/j.ipm.2025.104200_b28","doi-asserted-by":"crossref","first-page":"10985","DOI":"10.1109\/ACCESS.2023.3241345","article-title":"Dialogue logic aware and key utterance decoupling model for multi-party dialogue reading comprehension","volume":"11","author":"Yang","year":"2023","journal-title":"IEEE Access"},{"key":"10.1016\/j.ipm.2025.104200_b29","doi-asserted-by":"crossref","first-page":"10985","DOI":"10.1109\/ACCESS.2023.3241345","article-title":"Dialogue logic aware and key utterance decoupling model for multi-party dialogue reading comprehension","volume":"11","author":"Yang","year":"2023","journal-title":"IEEE Access"},{"key":"10.1016\/j.ipm.2025.104200_b30","series-title":"Proceedings of the 2020 conference on empirical methods in natural language processing","first-page":"3406","article-title":"Variational hierarchical dialog autoencoder for dialog state tracking data augmentation","author":"Yoo","year":"2020"},{"key":"10.1016\/j.ipm.2025.104200_b31","series-title":"Proceedings of the 29th international conference on computational linguistics","first-page":"5372","article-title":"Speaker-aware discourse parsing on multi-party dialogues","author":"Yu","year":"2022"},{"key":"10.1016\/j.ipm.2025.104200_b32","doi-asserted-by":"crossref","first-page":"3896","DOI":"10.1109\/TASLP.2023.3313885","article-title":"Multi-grained evidence inference for multi-choice reading comprehension","volume":"31","author":"Zhao","year":"2023","journal-title":"IEEE\/ACM Transactions on Audio, Speech, and Language Processing"},{"key":"10.1016\/j.ipm.2025.104200_b33","series-title":"2022 international joint conference on neural networks","first-page":"1","article-title":"An enhanced key-utterance interactive model with decouped auxiliary tasks for multi-party dialogue reading comprehension","author":"Zhu","year":"2022"}],"container-title":["Information Processing & Management"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0306457325001414?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0306457325001414?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,11,4]],"date-time":"2025-11-04T21:47:49Z","timestamp":1762292869000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0306457325001414"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9]]},"references-count":33,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2025,9]]}},"alternative-id":["S0306457325001414"],"URL":"https:\/\/doi.org\/10.1016\/j.ipm.2025.104200","relation":{},"ISSN":["0306-4573"],"issn-type":[{"value":"0306-4573","type":"print"}],"subject":[],"published":{"date-parts":[[2025,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"LOSDF: A logical optimization and semantic decoupling framework for question answering in multi-party conversations","name":"articletitle","label":"Article Title"},{"value":"Information Processing & Management","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ipm.2025.104200","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"104200"}}