Papers with Role-Playing Agents

3 papers
Tell Me What You Don’t Know: Enhancing Refusal Capabilities of Role-Playing Agents via Representation Space Analysis and Editing (2025.findings-acl)

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Challenge: Role-playing Agents (RPAs) struggle to recognize and respond to hard queries that conflict with their role-play knowledge.
Approach: They propose a lightweight representation editing approach that conveniently shifts conflicting requests to the rejection region, thereby enhancing the model’s refusal accuracy.
Outcome: The proposed model improves RPAs’ refusal ability of conflicting requests while maintaining their general role-playing capabilities.
ThinkPersona: Thinking with Persona Graphs for Faithful Individualized Role-Playing (2026.acl-long)

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Challenge: Large Language Models are increasingly utilized as role-playing agents to simulate personas in interactive settings.
Approach: They propose a role-playing agent trained to explicitly ground responses in individual identity.
Outcome: The proposed agent can generate persona-consistent responses in long-context dialogues while maintaining general instruction-following capabilities.
OmniCharacter: Towards Immersive Role-Playing Agents with Seamless Speech-Language Personality Interaction (2025.acl-long)

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Challenge: Existing methods focus on replicating dialogues in textual form, neglecting the role’s voice traits as a crucial effect in interaction, which tends to be more immersive experiences in realistic scenarios.
Approach: They propose a first seamless speech-language personality interaction model to achieve immersive RPAs with low latency.
Outcome: The proposed model exhibits role-specific personality traits and vocal traits throughout the interaction, enabling a mixture of speech and language responses.

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