Psy-CoT decomposes reasoning into Interaction Perception, Psychological Empathy, and Logical Construction while RAPO asymmetrically weights role-specific tokens during policy optimization, outperforming prior CoT and GRPO baselines on role-playing benchmarks.
Large Language Models are Superpositions of All Characters: Attaining Arbitrary Role-play via Self-Alignment
3 Pith papers cite this work. Polarity classification is still indexing.
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2026 3verdicts
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LM agents' changeable modules prevent persistent identity and sanction sensitivity, making reputation mechanisms structurally inapplicable and requiring protocol-based behavioral harnesses instead.
A theory-grounded taxonomy of eight communication roles enables scalable annotation via LLMs and outperforms baselines when predicting peer recognition in student teams and performance improvement on a public deliberation dataset.
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Improving General Role-Playing Agents via Psychology-Grounded Reasoning and Role-Aware Policy Optimization
Psy-CoT decomposes reasoning into Interaction Perception, Psychological Empathy, and Logical Construction while RAPO asymmetrically weights role-specific tokens during policy optimization, outperforming prior CoT and GRPO baselines on role-playing benchmarks.