Papers by Naipeng Chao

3 papers
Knowing-but-Doing: Diagnosing and Defending Role-Play-Driven LLMs Jailbreaks via Moral Disengagement (2026.findings-acl)

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Challenge: Large Language Models (LLMs) are increasingly used in role-play scenarios, but their safety implications remain under-characterized.
Approach: They propose a diagnostic benchmark for role-play jailbreaks based on Bandura’s Moral Disengagement theory and propose 'MD-Trace' based defense that reduces attack success while maintaining Role Fidelity.
Outcome: The proposed framework improves safety behavior for benign personas while increasing unsafe compliance for malicious ones.
Toward Consistent World Models with Multi-Token Prediction and Latent Semantic Enhancement (2026.acl-long)

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Challenge: Existing methods to learn internal world models rely on one-step supervision . however, standard MTP suffers from structural hallucinations .
Approach: They propose a method which anchors predictions to ground-truth hidden state trajectories.
Outcome: The proposed method bridges the gap between discrete tokens and continuous state representations, reducing structural hallucinations, and improving robustness to perturbations.
PersonaArena: Dynamic Simulation for Evaluating and Enhancing Persona-Level Role-Playing in Large Language Models (2026.findings-acl)

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Challenge: Existing research focuses on character-level settings and static evaluation formats fail to capture the complexity of everyday social interactions.
Approach: They propose a dynamic simulation framework for evaluating and improving persona-level role-playing in large language models (LLMs).
Outcome: The proposed framework leverages user-generated social content to construct a nuanced persona bank and elicits multi-turn, context-rich interactions within simulated social environments.

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