Papers by Xuda Zhi

2 papers
On Safety Risks in Experience-Driven Self-Evolving Agents (2026.findings-acl)

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Challenge: Experience-driven self-evolution has emerged as a promising paradigm for improving the autonomy of large language model agents, yet its reliance on self-curated experience introduces underexplored safety risks.
Approach: They investigate how experience accumulation and utilization in self-evolving agents affect safety performance across web-based and embodied environments.
Outcome: The findings expose inherent limitations of current self-evolving agents and call for more principled strategies to ensure safe and reliable adaptation.
When Personalization Legitimizes Risks: Uncovering Safety Vulnerabilities in Personalized Dialogue Agents (2026.acl-long)

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Challenge: Existing research on personalized LLM agents focuses on the effectiveness of personalized responses.
Approach: They propose a benchmark to quantify intent legitimation in personalized interactions . they propose 'detection-reflection' method that detects intent legititimation from internal representation space .
Outcome: The proposed method reduces safety degradation by using internal representation space.

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