Elamur Research⌕
☰
home / papers / 2026 / PERM: Psychology-grounded Empathetic Reward Modeling for Large Language Models

PERM: Psychology-grounded Empathetic Reward Modeling for Large Language Models

Paper · 2026 · Chengbing Wang, Wuqiang Zheng, Yang Zhang et al.

Summary

LLMs used in emotionally sensitive settings often give generic or overly solution-focused replies instead of real emotional support. Existing RL methods for improving empathy score responses from only one side: either the model's output or the user's reaction. PERM draws on Barrett-Lennard's Empathy Cycle theory, which treats empathy as a loop between a supporter and a seeker, and builds a reward that reflects both sides. On the supporter side, it scores Resonation (how well the model's internal analysis grasps the seeker's emotions, their causes, and hidden needs) and Expression (how warm, natural, and non-formulaic the reply is). On the seeker side, it scores Reception (whether the reply feels supportive to the user). A separate bystander judge checks general qualities such as coherence and relevance. LLMs were RL-trained with this combined reward on EmpatheticDialogues. They beat state-of-the-art baselines by more than 10% on an emotional intelligence benchmark and an industrial conversation set, and a blinded user study favoured them. The work shows that psychology-grounded, multi-perspective rewards produce more authentic empathetic replies.

Key points

  • The three empathy scores (Resonation, Expression, Reception) are merged with a harmonic mean. A weighted bystander reward is then added to form the final RL signal.
  • Training uses single-turn dialogues from EmpatheticDialogues with synthetic user personas (name, age, gender). Evaluation covers EQbench3 and an industrial daily-conversation benchmark, which the authors plan to release.
  • PERM improves on baselines by over 10%, and about 70% of participants in a blinded user study preferred its responses.
  • The baselines and related RL work include Partner, EmpRL, and RLVER, all of which rely on single-perspective rewards. Code is available at github.com/ZhengWwwq/PERM.
  • The authors list two main limitations: there is no multi-turn RL, and there is no user memory or preference modeling. Both are proposed as future work.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

 Institutions

🎓National University of SingaporeSingapore · Singapore180 works · 34,304 citations🎓University of Science and Technology of ChinaHefei · China108 works · 112,698 citations🏢Huawei TechnologiesShenzhen · China75 works · 12,975 citations

 Fields, topics and concepts

📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Computer Science · 16,667 worksArtificial Intelligence · 16,194 worksArts and Humanities · 16,039 worksLanguage and Linguistics · 15,891 worksPsychology · 1,552 worksExperimental and Cognitive Psychology · 870 works

Cite

Cite as Chengbing Wang, Wuqiang Zheng, Yang Zhang, Fengbin Zhu, Junyi Cheng, Yi Xie, Wenjie Wang and Fuli Feng. 2026. PERM: Psychology-grounded Empathetic Reward Modeling for Large Language Models. Findings of the Association for Computational Linguistics: ACL 2026.

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.18653/v1/2026.findings-acl.363

@inproceedings{wang2026perm,
  title = {{PERM: Psychology-grounded Empathetic Reward Modeling for Large Language Models}},
  author = {Chengbing Wang, Wuqiang Zheng, Yang Zhang, Fengbin Zhu, Junyi Cheng, Yi Xie, Wenjie Wang and Fuli Feng},
  booktitle = {Findings of the Association for Computational Linguistics: ACL 2026},
  year = {2026},
  doi = {10.18653/v1/2026.findings-acl.363},
  url = {https://doi.org/10.18653/v1/2026.findings-acl.363}
}

References

93 references, 35 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

  1. Reza Yazdani Aminabadi, Samyam Rajbhandari, Ammar Ahmad Awan, Cheng Li, Du Li, Elton Zheng, Olatunji Ruwase, Shaden Smith, Minjia Zhang, Jeff Rasley, and 1 others. 2022. Deepspeed-inference: enabling efficient inference of transformer models at unprecedented scale. In SC22: International Conference… find
  2. Yuntao Bai, Saurav Kadavath, Sandipan Kundu, Amanda Askell, Jackson Kernion, Andy Jones, Anna Chen, Anna Goldie, Azalia Mirhoseini, Cameron McKinnon, Carol Chen, Catherine Olsson, Christopher Olah, Danny Hernandez, Dawn Drain, Deep Ganguli, Dustin Li, Eli Tran-Johnson, Ethan Perez, and 32 others. 20… — Constitutional AI: Harmlessness from AI Feedback
  3. Godfrey T Barrett-Lennard. 1981. The empathy cycle: Refinement of a nuclear concept. Journal of counseling psychology, 28(2):91. find
  4. Suhas Bn, Yash Mahajan, Dominik O. Mattioli, Andrew M. Sherrill, Rosa I. Arriaga, Christopher Wiese, and Saeed Abdullah. 2025. The pursuit of empathy: Evaluating small language models for PTSD dialogue support. In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing… find
  5. Francine Chen, Scott A. Carter, Tatiana Lau, Nayeli Suseth Bravo, Sumanta Bhattacharyya, Kate A. Sieck, and Charlene C. Wu. 2025a. Empathy prediction from diverse perspectives. In ACL (1), pages 8959–8974. Association for Computational Linguistics. find
  6. Jiawei Chen, Yang Yang, Chao Yu, Yu Tian, Zhi Cao, Xue Yang, Linghao Li, Hang Su, and Zhaoxia Yin. 2025b. Red teaming large reasoning models. arXiv preprint arXiv:2512.00412.
  7. Yao Chen, Yilong Chen, Yinqi Yang, Junyuan Shang, Zhenyu Zhang, Zefeng Zhang, Shuaiyi Nie, Shuohuan Wang, Yu Sun, Hua Wu, HaiFeng Wang, and Tingwen Liu. 2026. Sparse growing transformer: Training-time sparse depth allocation via progressive attention looping. Preprint, arXiv:2603.23998. find
  8. Yao Chen, Jiawei Sheng, Wenyuan Zhang, and Tingwen Liu. 2025c. Improving reasoning capabilities in small models through mixture-of-layers distillation with stepwise attention on key information. In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, pages 4952– 49…
  9. Yirong Chen, Xiaofen Xing, Jingkai Lin, Huimin Zheng, Zhenyu Wang, Qi Liu, and Xiangmin Xu. 2023. Soulchat: Improving llms’ empathy, listening, and comfort abilities through fine-tuning with multi-turn empathy conversations. In EMNLP (Findings), pages 1170–1183. Association for Computational Linguis… find
  10. Tianzhe Chu, Yuexiang Zhai, Jihan Yang, Shengbang Tong, Saining Xie, Dale Schuurmans, Quoc V. Le, Sergey Levine, and Yi Ma. 2025. SFT memorizes, RL generalizes: A comparative study of foundation model post-training. In ICML. OpenReview.net.
  11. Ganqu Cui, Lifan Yuan, Ning Ding, Guanming Yao, Bingxiang He, Wei Zhu, Yuan Ni, Guotong Xie, Ruobing Xie, Yankai Lin, Zhiyuan Liu, and Maosong Sun. 2024. ULTRAFEEDBACK: boosting language models with scaled AI feedback. In ICML. OpenReview.net. find
  12. DeepSeek-AI. 2025. Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning. CoRR, abs/2501.12948.
  13. Wenhan Dong, Yuemeng Zhao, Zhen Sun, Yule Liu, Zifan Peng, Jingyi Zheng, Zongmin Zhang, Ziyi Zhang, Jun Wu, Ruiming Wang, Shengmin Xu, Xinyi Huang, and Xinlei He. 2025. Humanizing llms: A survey of psychological measurements with tools, datasets, and human-agent applications. CoRR, abs/2505.00049. — [arXiv:2505.00049](https://arxiv.org/abs/2505.00049) find
  14. Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Amy Yang, Angela Fan, and 1 others. 2024. The llama 3 herd of models. arXiv e-prints, pages arXiv–2407.
  15. Tuomas Haarnoja, Haoran Tang, Pieter Abbeel, and Sergey Levine. 2017. Reinforcement learning with deep energy-based policies. In ICML, Proceedings of Machine Learning Research, pages 1352–1361. PMLR. find
  16. Yuanyuan He, Yongsen Pan, Wei Li, Jiali You, Jiawen Deng, and Fuji Ren. 2025. ECC: An emotion-cause conversation dataset for empathy response. In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, pages 6011– 6028, Suzhou, China. Association for Computational Lin… find
  17. Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, Weizhu Chen, and 1 others. 2022. Lora: Low-rank adaptation of large language models. ICLR, 1(2):3.
  18. He Hu, Yucheng Zhou, Juzheng Si, Qianning Wang, Hengheng Zhang, Fuji Ren, Fei Ma, and Laizhong Cui. 2025. Beyond empathy: Integrating diagnostic and therapeutic reasoning with large language models for mental health counseling. CoRR, abs/2505.15715. — [arXiv:2505.15715](https://arxiv.org/abs/2505.15715) find
  19. Fanding Huang, Guanbo Huang, Xiao Fan, Yi He, Xiao Liang, Xiao Chen, Qinting Jiang, Faisal Nadeem Khan, Jingyan Jiang, and Zhi Wang. 2026. Semantic-space exploration and exploitation in rlvr for llm reasoning. Preprint, arXiv:2509.23808. find
  20. Aaron Hurst, Adam Lerer, Adam P. Goucher, Adam Perelman, Aditya Ramesh, Aidan Clark, AJ Ostrow, Akila Welihinda, Alan Hayes, Alec Radford, Aleksander Madry, Alex Baker-Whitcomb, Alex Beutel, Alex Borzunov, Alex Carney, Alex Chow, Alex Kirillov, Alex Nichol, Alex Paino, and 79 others. 2024. Gpt-4o sy…
  21. Lujain Ibrahim, Franziska Sofia Hafner, and Luc Rocher. 2025. Training language models to be warm and empathetic makes them less reliable and more sycophantic. CoRR, abs/2507.21919. — [arXiv:2507.21919](https://arxiv.org/abs/2507.21919) find
  22. Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Hao Yu, Joseph Gonzalez, Hao Zhang, and Ion Stoica. 2023. Efficient memory management for large language model serving with pagedattention. In Proceedings of the 29th symposium on operating systems principles, pages 611–626.
  23. Yu Li, Tian Lan, and Zhengling Qi. 2025. Inspo: Unlocking intrinsic self-reflection for llm preference optimization. arXiv preprint arXiv:2512.23126. — [arXiv:2512.23126](https://arxiv.org/abs/2512.23126) find
  24. Yu Li, Tian Lan, and Zhengling Qi. 2026a. When right meets wrong: Bilateral context conditioning with reward-confidence correction for grpo. arXiv preprint arXiv:2603.13134. — [arXiv:2603.13134](https://arxiv.org/abs/2603.13134) find
  25. Yu Li, Rui Miao, Zhengling Qi, and Tian Lan. 2026b. Arise: Agent reasoning with intrinsic skill evolution in hierarchical reinforcement learning. arXiv preprint arXiv:2603.16060. — [arXiv:2603.16060](https://arxiv.org/abs/2603.16060) find
  26. Jian Liao, Yu Feng, Yujin Zheng, Jun Zhao, Suge Wang, and Jianxing Zheng. 2025. My words imply your opinion: Reader agent-based propagation enhancement for personalized implicit emotion analysis. In ACL (1), pages 16156–16172. Association for Computational Linguistics. find
  27. Chris Yuhao Liu, Liang Zeng, Yuzhen Xiao, Jujie He, Jiacai Liu, Chaojie Wang, Rui Yan, Wei Shen, Fuxiang Zhang, Jiacheng Xu, Yang Liu, and Yahui Zhou. 2025a. Skywork-reward-v2: Scaling preference data curation via human-ai synergy. CoRR, abs/2507.01352.
  28. Hongye Liu and Ricardo Henao. 2025. Learning to substitute words with model-based score ranking. In Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), pages 11551–11565. find
  29. June M. Liu, Donghao Li, He Cao, Tianhe Ren, Zeyi Liao, and Jiamin Wu. 2023. Chatcounselor: A large language models for mental health support. CoRR, abs/2309.15461. — [arXiv:2309.15461](https://arxiv.org/abs/2309.15461) find
  30. Tao Liu, Taiqiang Wu, Runming Yang, Shaoning Sun, Junjie Wang, and Yujiu Yang. 2026. Profit: Leveraging high-value signals in sft via probability-guided token selection. arXiv preprint arXiv:2601.09195.
  31. Tingting Liu, Salvatore Giorgi, Ankit Aich, Allison Lahnala, Brenda Curtis, Lyle H. Ungar, and João Sedoc. 2025b. The illusion of empathy: How AI chatbots shape conversation perception. In AAAI, pages 14327–14335. AAAI Press. find
  32. Weichu Liu, Jing Xiong, Yuxuan Hu, Zixuan Li, Minghuan Tan, Ningning Mao, Chenyang Zhao, Zhongwei Wan, Chaofan Tao, Wendong Xu, Hui Shen, Chengming Li, Lingpeng Kong, and Ngai Wong. 2025c. Longemotion: Measuring emotional intelligence of large language models in long-context interaction. CoRR, abs/2… — [arXiv:2509.07403](https://arxiv.org/abs/2509.07403) find
  33. Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019. Roberta: A robustly optimized BERT pretraining approach. CoRR, abs/1907.11692.
  34. Guanran Luo, Zhongquan Jian, Wentao Qiu, Meihong Wang, and Qingqiang Wu. 2025. DTCRS: Dynamic tree construction for recursive summarization. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 10948–10963, Vienna, Austria. Associa… find
  35. Guanran Luo, Wentao Qiu, Zhongquan Jian, Meihong Wang, and Qingqiang Wu. 2026a. Gcot-decoding: Unlocking deep reasoning paths for universal question answering. Preprint, arXiv:2604.06794.
  36. Guanran Luo, Wentao Qiu, Wanru Zhao, Wenhan Lv, Zhongquan Jian, Meihong Wang, and Qingqiang Wu. 2026b. Agsc: Adaptive granularity and semantic clustering for uncertainty quantification in long-text generation. Preprint, arXiv:2604.06812.
  37. Hui Ma, Bo Zhang, Bo Xu, Jian Wang, Hongfei Lin, and Xiao Sun. 2025. Empathy level alignment via reinforcement learning for empathetic response generation. IEEE Trans. Affect. Comput., 16(3):1873–1884. find
  38. Ananya Malik, Nazanin Sabri, Melissa Karnaze, and Mai ElSherief. 2025a. Are llms empathetic to all? investigating the influence of multi-demographic personas on a model’s empathy. CoRR, abs/2510.10328. find
  39. Saumya Malik, Valentina Pyatkin, Sander Land, Jacob Morrison, Noah A. Smith, Hannaneh Hajishirzi, and Nathan Lambert. 2025b. Rewardbench 2: Advancing reward model evaluation. CoRR, abs/2506.01937. — [arXiv:2506.01937](https://arxiv.org/abs/2506.01937) find
  40. Shervin Minaee, Tomás Mikolov, Narjes Nikzad, Meysam Chenaghlu, Richard Socher, Xavier Amatriain, and Jianfeng Gao. 2024. Large language models: A survey. CoRR, abs/2402.06196.
  41. Jared Moore, Declan Grabb, William Agnew, Kevin Klyman, Stevie Chancellor, Desmond C. Ong, and Nick Haber. 2025. Expressing stigma and inappropriate responses prevents llms from safely replacing mental health providers. In FAccT, pages 599–627. ACM. find
  42. Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll L. Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul F. Christiano, Jan Leike, and Ryan Lowe. 2022.… — Training language models to follow instructions with human feedback
  43. Samuel J. Paech. 2023. Eq-bench: An emotional intelligence benchmark for large language models. Preprint, arXiv:2312.06281.
  44. Samuel J. Paech. 2025. Eq-bench 3: Emotional intelligence benchmark. https://github.com/ EQ-bench/eqbench3. ↗
  45. Pat Pataranutaporn, Sheer Karny, Chayapatr Archi-waranguprok, Constanze Albrecht, Auren R. Liu, and Pattie Maes. 2025. "my boyfriend is ai": A computational analysis of human-ai companionship in reddit’s AI community. CoRR, abs/2509.11391. — [arXiv:2509.11391](https://arxiv.org/abs/2509.11391) find
  46. Yilun Qiu, Tianhao Shi, Xiaoyan Zhao, Fengbin Zhu, Yang Zhang, and Fuli Feng. 2025a. Latent inter-user difference modeling for llm personalization. In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, pages 10610– 10628.
  47. Yilun Qiu, Xiaoyan Zhao, Yang Zhang, Yimeng Bai, Wenjie Wang, Hong Cheng, Fuli Feng, and Tat-Seng Chua. 2025b. Measuring what makes you unique: Difference-aware user modeling for enhancing llm personalization. In Findings of the Association for Computational Linguistics: ACL 2025, pages 21258– 21277… find
  48. Nisan Stiennon, Long Ouyang, Jeffrey Wu, Daniel M. Ziegler, Ryan Lowe, Chelsea Voss, Alec Radford, Dario Amodei, and Paul F. Christiano. 2020. Learning to summarize with human feedback. In NeurIPS. find
  49. Jina Suh, Lindy Le, Erfan Shayegani, Gonzalo A. Ramos, Judith Amores, Desmond C. Ong, Mary Czerwinski, and Javier Hernandez. 2025. SENSE-7: taxonomy and dataset for measuring user perceptions of empathy in sustained human-ai conversations. CoRR, abs/2509.16437. — [arXiv:2509.16437](https://arxiv.org/abs/2509.16437) find
  50. Hao Sun, Zhenru Lin, Chujie Zheng, Siyang Liu, and Minlie Huang. 2021. Psyqa: A chinese dataset for generating long counseling text for mental health support. In ACL/IJCNLP (Findings), volume ACL/I-JCNLP 2021 of Findings of ACL, pages 1489–1503. Association for Computational Linguistics. find
  51. Yuxi Sun, Aoqi Zuo, Wei Gao, and Jing Ma. 2025. Causalabstain: Enhancing multilingual llms with causal reasoning for trustworthy abstention. In Findings of the Association for Computational Linguistics: ACL 2025, pages 14060–14076. find
  52. Quan Tu, Yanran Li, Jianwei Cui, Bin Wang, Ji-Rong Wen, and Rui Yan. 2022. MISC: A mixed strategy-aware model integrating COMET for emotional support conversation. In ACL (1), pages 308–319. Association for Computational Linguistics.
  53. Leandro von Werra, Younes Belkada, Lewis Tunstall, Edward Beeching, Tristan Thrush, Nathan Lambert, Shengyi Huang, Kashif Rasul, and Quentin Gallouédec. 2020. Trl: Transformer reinforcement learning. https://github.com/huggingface/trl. ↗
  54. Hannah Rashkin, Eric Michael Smith, Margaret Li, and Y-Lan Boureau. 2019. Towards empathetic open-domain conversation models: A new benchmark and dataset. In ACL (1), pages 5370–5381. Association for Computational Linguistics. find
  55. Chengbing Wang, Yang Zhang, Wenjie Wang, Xiaoyan Zhao, Fuli Feng, Xiangnan He, and Tat-Seng Chua. 2026a. Think-while-generating: On-the-fly reasoning for personalized long-form generation. Preprint, arXiv:2512.06690. — [arXiv:2512.06690](https://arxiv.org/abs/2512.06690) find
  56. Zhihong Shao, Peiyi Wang, Qihao Zhu, Runxin Xu, Junxiao Song, Mingchuan Zhang, Y. K. Li, Y. Wu, and Daya Guo. 2024. Deepseekmath: Pushing the limits of mathematical reasoning in open language models. CoRR, abs/2402.03300.
  57. Chengbing Wang, Yang Zhang, Fengbin Zhu, Jizhi Zhang, Tianhao Shi, and Fuli Feng. 2025a. Leveraging memory retrieval to enhance llm-based generative recommendation. In Companion Proceedings of the ACM on Web Conference 2025, pages 1346–1350. find
  58. Ashish Sharma, Inna W. Lin, Adam S. Miner, David C. Atkins, and Tim Althoff. 2021. Towards facilitating empathic conversations in online mental health support: A reinforcement learning approach. In WWW, pages 194–205. ACM / IW3C2. find
  59. Peisong Wang, Ruotian Ma, Bang Zhang, Xingyu Chen, Zhiwei He, Kang Luo, Qingsong Lv, Qingxuan Jiang, Zheng Xie, Shanyi Wang, Yuan Li, Fanghua Ye, Jian Li, Yifan Yang, Zhaopeng Tu, and Xiaolong Li. 2025b. RLVER: reinforcement learning with verifiable emotion rewards for empathetic agents. CoRR, abs/2… — [arXiv:2507.03112](https://arxiv.org/abs/2507.03112) find
  60. Yuhao Shen, Tianyu Liu, Junyi Shen, Jinyang Wu, Quan Kong, Li Huan, and Cong Wang. 2026. Double: Breaking the acceleration limit via double retrieval speculative parallelism. arXiv preprint arXiv:2601.05524. find
  61. Adarsh Srinivasan, Jacob Dineen, Muhammad Umar Afzal, Muhammad Uzair Sarfraz, Irbaz B. Riaz, and Ben Zhou. 2025. RECAP: transparent inference-time emotion alignment for medical dialogue systems. CoRR, abs/2509.10746.
  62. Tianyi Wang, Long Li, Hongcan Guo, Yibiao Chen, Yixia Li, Yong Wang, Yun Chen, and Guanhua Chen. 2026b. Anchored policy optimization: Mitigating exploration collapse via support-constrained rectification. Preprint, arXiv:2602.05717. — [arXiv:2602.05717](https://arxiv.org/abs/2602.05717) find
  63. Tianyi Wang, Yixia Li, Long Li, Yibiao Chen, Shaohan Huang, Yun Chen, Peng Li, Yang Liu, and Guanhua Chen. 2026c. Sppo: Sequence-level ppo for long-horizon reasoning tasks. arXiv:2604.08865.
  64. Preprint, Tongxi Wang. 2026. Fbs: Modeling native parallel reading inside a transformer. arXiv preprint arXiv:2601.21708.
  65. Yu Wang, Emmanuele Chersoni, and Chu-Ren Huang. 2026d. This one or that one? a study on accessibility via demonstratives with multimodal large language models. In Language Resources and Evaluation Conference 2026. European Language Resources Association (ELRA).
  66. Jinyang Wu, Shuo Yang, Changpeng Yang, Yuhao Shen, Shuai Zhang, Zhengqi Wen, and Jianhua Tao. 2026. Spark: Strategic policy-aware exploration via dynamic branching for long-horizon agentic learning. arXiv preprint arXiv:2601.20209.
  67. Shenghan Wu, Yimo Zhu, Wynne Hsu, Mong-Li Lee, and Yang Deng. 2025a. From personas to talks: Revisiting the impact of personas on LLM-synthesized emotional support conversations. In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, pages 5439–5453, Suzhou, China… find
  68. Shirley Wu, Michel Galley, Baolin Peng, Hao Cheng, Gavin Li, Yao Dou, Weixin Cai, James Zou, Jure Leskovec, and Jianfeng Gao. 2025b. Collabllm: From passive responders to active collaborators. In ICML. OpenReview.net. find
  69. Shijia Xu, Yu Wang, Xiaolong Jia, Zhou Wu, Kai Liu, and April Xiaowen Dong. 2026a. Rcbsf: A multi-agent framework for automated contract revision via stackelberg game. Preprint, arXiv:2604.10740.
  70. Jiahao Yuan, Zhiqing Cui, Hanqing Wang, Yuansheng Gao, Yucheng Zhou, and Usman Naseem. 2025. Kardia-r1: Unleashing llms to reason toward understanding and empathy for emotional support via rubric-as-judge reinforcement learning. CoRR, abs/2512.01282. — [arXiv:2512.01282](https://arxiv.org/abs/2512.01282) find
  71. Weizhe Yuan, Richard Yuanzhe Pang, Kyunghyun Cho, Xian Li, Sainbayar Sukhbaatar, Jing Xu, and Jason Weston. 2024. Self-rewarding language models. In ICML. OpenReview.net. find
  72. Marc Zao-Sanders. 2025. How people are really using gen ai in 2025. find
  73. Harvard Business Review (2025). find
  74. Bang Zhang, Ruotian Ma, Qingxuan Jiang, Peisong Wang, Jiaqi Chen, Zheng Xie, Xingyu Chen, Yue Wang, Fanghua Ye, Jian Li, Yifan Yang, Zhaopeng Tu, and Xiaolong Li. 2025a. Sentient agent as a judge: Evaluating higher-order social cognition in large language models. CoRR, abs/2505.02847.
  75. Jiaquan Zhang, Qigan Sun, Chaoning Zhang, Xudong Wang, Zhenzhen Huang, Yitian Zhou, Pengcheng Zheng, Chi lok Andy Tai, Sung-Ho Bae, Zeyu Ma, Caiyan Qin, Jinyu Guo, Yang Yang, and Hengtao Shen. 2026a. Tda-rc: Task-driven alignment for knowledge-based reasoning chains in large language models. Preprin… — [arXiv:2604.04942](https://arxiv.org/abs/2604.04942) find
  76. Jiaquan Zhang, Chaoning Zhang, Shuxu Chen, Zhenzhen Huang, Pengcheng Zheng, Zhicheng Wang, Ping Guo, Fan Mo, Sung-Ho Bae, Jie Zou, Jiwei Wei, and Yang Yang. 2026b. Lightweight llm agent memory with small language models. Preprint, arXiv:2604.07798.
  77. Shijia Xu, Zhou Wu, Xiaolong Jia, Yu Wang, Kai Liu, and April Xiaowen Dong. 2026b. Self-correcting rag: Enhancing faithfulness via mmkp context selection and nli-guided mcts. Preprint, arXiv:2604.10734.
  78. Jiaquan Zhang, Chaoning Zhang, Shuxu Chen, Yibei Liu, Chenghao Li, Qigan Sun, Shuai Yuan, Fach-rina Dewi Puspitasari, Dongshen Han, Guoqing Wang, and 1 others. 2026c. Text summarization via global structure awareness. arXiv preprint arXiv:2602.09821. — [arXiv:2602.09821](https://arxiv.org/abs/2602.09821) find
  79. Yangyang Xu, Jinpeng Hu, Zhuoer Zhao, Zhangling Duan, Xiao Sun, and Xun Yang. 2025a. MultiAgentESC: A LLM-based multi-agent collaboration framework for emotional support conversation. In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, pages 4665–4681, Suzhou,… find
  80. Jiaquan Zhang, Chaoning Zhang, Shuxu Chen, Xudong Wang, Zhenzhen Huang, Pengcheng Zheng, Shuai Yuan, Sheng Zheng, Qigan Sun, Jie Zou, and 1 others. 2026d. Learning global hypothesis space for enhancing synergistic reasoning chain. arXiv preprint arXiv:2602.09794. — [arXiv:2602.09794](https://arxiv.org/abs/2602.09794) find
  81. Yiyan Xu, Wenjie Wang, Yang Zhang, Biao Tang, Peng Yan, Fuli Feng, and Xiangnan He. 2025b. Personalized image generation with large multimodal models. In Proceedings of the ACM on Web Conference 2025, pages 264–274. find
  82. An Yang, Anfeng Li, Baosong Yang, Beichen Zhang, Binyuan Hui, Bo Zheng, Bowen Yu, Chang Gao, Chengen Huang, Chenxu Lv, and 1 others. 2025. Qwen3 technical report. arXiv preprint arXiv:2505.09388.
  83. Naifan Zhang, Ruihan Sun, Ruixi Su, Shiqi Ma, Shiya Zhang, Xianna Weng, Xiaofan Zhang, Yuhan Zhan, Yuyang Xu, Zhaohan Chen, and 1 others. 2025b. Echo-n1: Affective rl frontier. arXiv preprint arXiv:2512.00344. — [arXiv:2512.00344](https://arxiv.org/abs/2512.00344) find
  84. Qianchi Zhang, Hainan Zhang, Liang Pang, Yongxin Tong, Hongwei Zheng, and Zhiming Zheng. 2026e. Less is more: Compact clue selection for efficient retrieval-augmented generation reasoning. In Proceedings of the ACM Web Conference 2026, pages 1971–1982. find
  85. Qianchi Zhang, Hainan Zhang, Liang Pang, Hongwei Zheng, and Zhiming Zheng. 2026f. Stable-rag: Mitigating retrieval-permutation-induced hallucinations in retrieval-augmented generation. arXiv preprint arXiv:2601.02993.
  86. Xinglang Zhang, Yunyao Zhang, ZeLiang Chen, Junqing Yu, Wei Yang, and Zikai Song. 2026g. Logical phase transitions: Understanding collapse in llm logical reasoning. arXiv preprint arXiv:2601.02902.
  87. Yunyao Zhang, Xinglang Zhang, Junxi Sheng, Wenbing Li, Junqing Yu, Yi-Ping Phoebe Chen, Wei Yang, and Zikai Song. 2026h. Semantic-aware logical reasoning via a semiotic framework. Preprint, arXiv:2509.24765.
  88. Zeyu Zhang, Yang Zhang, Haoran Tan, Rui Li, and Xu Chen. 2025c. Explicit vs implicit memory: Exploring multi-hop complex reasoning over personalized information. arXiv preprint arXiv:2508.13250. — [arXiv:2508.13250](https://arxiv.org/abs/2508.13250) find
  89. Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Xiaolei Wang, Yupeng Hou, Yingqian Min, Beichen Zhang, Junjie Zhang, Zican Dong, Yifan Du, Chen Yang, Yushuo Chen, Zhipeng Chen, Jinhao Jiang, Ruiyang Ren, Yifan Li, Xinyu Tang, Zikang Liu, and 3 others. 2023. A survey of large language models. CoRR,…
  90. Xiaoyan Zhao, Juntao You, Yang Zhang, Wenjie Wang, Hong Cheng, Fuli Feng, See-Kiong Ng, and Tat-Seng Chua. 2025. Nextquill: Causal preference modeling for enhancing llm personalization. arXiv preprint arXiv:2506.02368. — [arXiv:2506.02368](https://arxiv.org/abs/2506.02368) find
  91. Ziyi Zhao, Chongming Gao, Yang Zhang, Haoyan Liu, Weinan Gan, Huifeng Guo, Yong Liu, and Fuli Feng. 2026. Don’t start over: A cost-effective framework for migrating personalized prompts between llms. arXiv preprint arXiv:2601.12034. — [arXiv:2601.12034](https://arxiv.org/abs/2601.12034) find
  92. Chujie Zheng, Sahand Sabour, Jiaxin Wen, Zheng Zhang, and Minlie Huang. 2023a. Augesc: Dialogue augmentation with large language models for emotional support conversation. In ACL (Findings), pages 1552–1568. Association for Computational Linguistics. find
  93. Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric P. Xing, Hao Zhang, Joseph E. Gonzalez, and Ion Stoica. 2023b. Judging llm-as-a-judge with mt-bench and chatbot arena. In NeurIPS.

Updated

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/papers/wang-2026-perm-psychology-grounded-empathetic-reward/