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In recent years, with the rapid advancements in large language models (LLMs), achieving excellent empathetic response capabilities has become a crucial prerequisite.
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COMET: Commonsense Transformers for Automatic Knowledge Graph Construction. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics . 4762–4779
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MoEL: Mixture of Empathetic Listeners. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) . 121–132
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Probing commonsense explanation in dialogue response generation. In Findings of the Association for Computational Linguistics: EMNLP 2021 . 4132–4146
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Wish I Can Feel What You Feel: A Neural Approach for Empathetic Response Generation. In Findings of the Association for Computational Linguistics: EMNLP 2022 . 922–933
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Emp-RFT: Empathetic Response Generation via Recognizing Feature Transitions between Utterances. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies . 4118–4128
Wongyu Kim, Youbin Ahn, Donghyun Kim, and Kyong-Ho Lee. 2022 · 2022
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Knowledge bridging for empathetic dialogue generation. In Proceedings of the AAAI Conference on Artificial Intelligence , Vol. 36. 10993–11001
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Cem: Commonsense-aware empathetic response generation. In Proceedings of the AAAI Conference on Artificial Intelligence , Vol. 36. 11229–11237
Sahand Sabour, Chujie Zheng, and Minlie Huang. 2022 · 2022
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Empathetic Dialogue Generation via Sensitive Emotion Recognition and Sensible Knowledge Selection. In Findings of the Association for Computational Linguistics: EMNLP 2022 . 4634–4645
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Alpagasus: Training a better alpaca with fewer data
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How large language models will disrupt data management
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E-CORE: Emotion Correlation Enhanced Empathetic Dialogue Generation. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing . 10568–10586
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Self-Alignment with Instruction Backtranslation
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Differentially Private Synthetic Data via Foundation Model APIs 1: Images
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Baize: An Open-Source Chat Model with Parameter-Efficient Tuning on Self-Chat Data. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, EMNLP 2023, Singapore, December 6-10, 2023 . 6268–6278
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RefGPT: Dialogue Generation of GPT, by GPT, and for GPT. In Findings of the Association for Computational Linguistics: EMNLP 2023, Singapore, December 6-10, 2023 . Association for Computational Linguistics, 2511–2535
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Exploiting Emotion-Semantic Correlations for Empathetic Response Generation. In Findings of the Association for Computational Linguistics: EMNLP 2023 . 4826–4837
Zhou Yang, Zhaochun Ren, Wang Yufeng, Xiaofei Zhu, Zhihao Chen, Tiecheng Cai, Wu Yunbing, Yisong Su, Sibo Ju, and Xiangwen Liao. 2023a · 2023
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Don’t Lose Yourself! Empathetic Response Generation via Explicit Self-Other Awareness. In Findings of the Association for Computational Linguistics: ACL 2023 . 13331–13344
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Wei Liu, Weihao Zeng, Keqing He, Yong Jiang, and Junxian He. 2023 · 2023
Cited alongside, same era.
MUFFIN: Curating Multi-Faceted Instructions for Improving Instruction-Following
Renze Lou, Kai Zhang, Jian Xie, Yuxuan Sun, Janice Ahn, Hanzi Xu, Yu Su, and Wenpeng Yin. 2023 · 2023
Cited alongside, same era.
# InsTag: Instruction Tagging for Analyzing Supervised Fine-tuning of Large Language Models. In The Twelfth International Conference on Learning Representations
Keming Lu, Hongyi Yuan, Zheng Yuan, Runji Lin, Junyang Lin, Chuanqi Tan, Chang Zhou, and Jingren Zhou. 2023 · 2023
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Flexmoe: Scaling large-scale sparse pre-trained model training via dynamic device placement
Xiaonan Nie, Xupeng Miao, Zilong Wang, Zichao Yang, Jilong Xue, Lingxiao Ma, Gang Cao, and Bin Cui. 2023 · 2023
Cited alongside, same era.
GPT-4 technical report
R OpenAI. 2023b · 2023
Cited alongside, same era.
Think Twice: A Human-like Two-Stage Conversational Agent for Emotional Response Generation. In Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems . 727–736
Yushan Qian, Bo Wang, Shangzhao Ma, Wu Bin, Shuo Zhang, Dongming Zhao, Kun Huang, and Yuexian Hou. 2023a · 2023
Cited alongside, same era.
Harnessing the Power of Large Language Models for Empathetic Response Generation: Empirical Investigations and Improvements. In Findings of the Association for Computational Linguistics: EMNLP 2023 . 6516–6528
Yushan Qian, Weinan Zhang, and Ting Liu. 2023b · 2023
Cited alongside, same era.
Rational Sensibility: LLM Enhanced Empathetic Response Generation Guided by Self-presentation Theory
Linzhuang Sun, Nan Xu, Jingxuan Wei, Bihui Yu, Liping Bu, and Yin Luo. 2023 · 2023
Cited alongside, same era.
Weixiang Zhao, Yanyan Zhao, Xin Lu, and Bing Qin. 2023 · 2023
Later among the works it cites.
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 . 8223–8237
Jinfeng Zhou, Chujie Zheng, Bo Wang, Zheng Zhang, and Minlie Huang. 2023 · 2023
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A Survey of Multimodal Large Language Model from A Data-centric Perspective
Tianyi Bai, Hao Liang, Binwang Wan, Ling Yang, Bozhou Li, Yifan Wang, Bin Cui, Conghui He, Binhang Yuan, and Wentao Zhang. 2024 · 2024
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Run-Ze Fan, Xuefeng Li, Haoyang Zou, Junlong Li, Shwai He, Ethan Chern, Jiewen Hu, and Pengfei Liu. 2024 · 2024
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Cross-Modality Jailbreak and Mismatched Attacks on Medical Multimodal Large Language Models
Xijie Huang, Xinyuan Wang, Hantao Zhang, Jiawen Xi, Jingkun An, Hao Wang, and Chengwei Pan. 2024 · 2024
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Introducing Meta Llama 3: The most capable openly available LLM to date
meta llama. 2024 · 2024
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Demystifying Data Management for Large Language Models. In Companion of the 2024 International Conference on Management of Data . 547–555
Xupeng Miao, Zhihao Jia, and Bin Cui. 2024 · 2024
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SelectLLM: Can LLMs Select Important Instructions to Annotate?
Ritik Sachin Parkar, Jaehyung Kim, Jong Inn Park, and Dongyeop Kang. 2024 · 2024
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Efficient-Empathy: Towards Efficient and Effective Selection of Empathy Data
Linzhuang Sun, Hao Liang, Jingxuan Wei, Linkun Sun, Bihui Yu, Bin Cui, and Wentao Zhang. 2024 · 2024
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Do Generated Data Always Help Contrastive Learning?
Yifei Wang, Jizhe Zhang, and Yisen Wang. 2024 · 2024
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Differentially Private Synthetic Data via Foundation Model APIs 2: Text
Chulin Xie, Zinan Lin, Arturs Backurs, Sivakanth Gopi, Da Yu, Huseyin A. Inan, Harsha Nori, Haotian Jiang, Huishuai Zhang, Yin Tat Lee, Bo Li, and Sergey Yekhanin. 2024 · 2024
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An Iterative Associative Memory Model for Empathetic Response Generation
Zhou Yang, Zhaochun Ren, Yufeng Wang, Chao Chen, Haizhou Sun, Xiaofei Zhu, and Xiangwen Liao. 2024 · 2024
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CTSM: Combining Trait and State Emotions for Empathetic Response Model
Wang Yufeng, Chen Chao, Yang Zhou, Wang Shuhui, and Liao Xiangwen. 2024 · 2024
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