{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T22:40:28Z","timestamp":1773528028945,"version":"3.50.1"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,8]]},"abstract":"<jats:p>Emotion recognition in conversation,  which aims to predict the emotion for all utterances,  has attracted considerable research attention in recent years. It is a challenging task since the  recognition of the emotion in one  utterance  involves many complex factors, such as the conversational context, the speaker's  background, and the subtle difference between emotion labels. In this paper, we propose a novel framework which mimics the thinking process when modeling these factors. Specifically, we first comprehend the conversational context with a history-oriented prompt to selectively gather  information from predecessors of the target utterance. We then  model the speaker's background with an experience-oriented prompt  to retrieve the similar utterances from all conversations.  We finally  differentiate the subtle label semantics with a paraphrasing mechanism  to elicit the intrinsic label related knowledge.\n\nWe conducted extensive experiments on three benchmarks. The empirical results demonstrate the superiority of our proposed framework over the state-of-the-art baselines.<\/jats:p>","DOI":"10.24963\/ijcai.2023\/699","type":"proceedings-article","created":{"date-parts":[[2023,8,11]],"date-time":"2023-08-11T04:31:30Z","timestamp":1691728290000},"page":"6299-6307","source":"Crossref","is-referenced-by-count":17,"title":["Mimicking the Thinking Process for Emotion Recognition in Conversation with Prompts and Paraphrasing"],"prefix":"10.24963","author":[{"given":"Ting","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Computer Science, Wuhan University"}]},{"given":"Zhuang","family":"Chen","sequence":"additional","affiliation":[{"name":"The CoAI group, DCST, Tsinghua University"}]},{"given":"Ming","family":"Zhong","sequence":"additional","affiliation":[{"name":"School of Computer Science, Wuhan University"}]},{"given":"Tieyun","family":"Qian","sequence":"additional","affiliation":[{"name":"School of Computer Science, Wuhan University"},{"name":"Intellectual Computing Laboratory For Cultural Heritage, Wuhan University"}]}],"member":"10584","event":{"name":"Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}","theme":"Artificial Intelligence","location":"Macau, SAR China","acronym":"IJCAI-2023","number":"32","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2023,8,19]]},"end":{"date-parts":[[2023,8,25]]}},"container-title":["Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2023,8,11]],"date-time":"2023-08-11T04:54:07Z","timestamp":1691729647000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2023\/699"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2023,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2023\/699","relation":{},"subject":[],"published":{"date-parts":[[2023,8]]}}}