| Challenge: | Recent advances in reasoning and long-context memory are making large language models (LLMs) appear increasingly human-like, which has led researchers to adopt LLM agents as a substrate for social simulation. |
| Approach: | They propose a framework for emotionally stateful agents that integrates continuous Pleasure-Arousal-Dominance representation, dual-speed emotion dynamics, and emotion–memory coupling. |
| Outcome: | The proposed framework improves emotional grounded behavior, boosting communication, and emotional continuity across thousands of interactions over multiple base models and evaluators. |
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| Challenge: | Existing strategies focus on planning the next-turn dialogue strategies, while external strategy planners focus on generating empathetic responses. |
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Bang Zhang, Ruotian Ma, Qingxuan Jiang, Peisong Wang, Jiaqi Chen, Zheng Xie, Xingyu Chen, Yue Wang, Fanghua Ye, Jian Li, Yifan Yang, Zhaopeng Tu, Xiaolong Li
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| Challenge: | EmoCharacter evaluates emotional fidelity of role-playing agents in dialogues . current evaluations focus on personality fidelity, tone imitation, and knowledge consistency . |
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Dynamic Personality in LLM Agents: A Framework for Evolutionary Modeling and Behavioral Analysis in the Prisoner’s Dilemma (2025.findings-acl)
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| Challenge: | Current models rely on static personality traits but lack natural selection processes and direct psychological metrics, failing to accurately capture authentic dynamic personality variations. |
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