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Emotional Support Conversation (ESC) systems are pivotal in providing empathetic interactions, aiding users through negative emotional states by understanding and addressing their unique experiences.
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Exemplars-guided Empathetic Response Generation Controlled by the Elements of Human Communication
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Knowledge-enhanced Mixed-initiative Dialogue System for Emotional Support Conversations. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , Anna Rogers, Jordan Boyd-Graber, and Naoaki Okazaki (Eds.). Association for Computational Linguistics, Toronto, Canada, 4079–4095
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EmoUS: Simulating User Emotions in Task-Oriented Dialogues. In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval . 2526–2531
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Fado: Feedback-aware double controlling network for emotional support conversation
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TransESC: Smoothing Emotional Support Conversation via Turn-Level State Transition. In Findings of the Association for Computational Linguistics: ACL 2023 , Anna Rogers, Jordan Boyd-Graber, and Naoaki Okazaki (Eds.). Association for Computational Linguistics, Toronto, Canada, 6725–6739
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CASE: Aligning Coarse-to-Fine Cognition and Affection for Empathetic Response Generation. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , Anna Rogers, Jordan Boyd-Graber, and Naoaki Okazaki (Eds.). Association for Computational Linguistics, Toronto, Canada, 8223–8237
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Data-Juicer: A One-Stop Data Processing System for Large Language Models. In International Conference on Management of Data
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DQ-HGAN: A heterogeneous graph attention network based deep Q-learning for emotional support conversation generation
Ge Li, Mingyao Wu, Chensheng Wang, and Zhuo Liu. 2024 · 2024
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