Papers by Tianzhuo Yang

2 papers
SafeMCP: Proactive Power Regulation for LLM Agent Defense via Environment-Grounded Look-Ahead Reasoning (2026.acl-long)

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Challenge: Large Language Model (LLM) agents are expanding their action spaces to operate in complex environments.
Approach: They propose a server-side defense plugin that constrains tool acquisition via predictive reasoning regarding future safety risks.
Outcome: Experiments on PowerSeeking Bench, ToolEmu, and AgentHarm show that SafeMCP achieves a safe equilibrium, effectively mitigating risks while preserving agent utility.
A Game-Theoretica Negotiation Framework for Cross-Cultural Consensus (2026.acl-long)

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Challenge: Large language models exhibit pronounced WEIRD cultural bias, marginalizing diverse viewpoints and posing challenges for reconciling diverse populations with varying cultural backgrounds and value systems.
Approach: They propose a framework for cross-cultural fairness using a Nash Equilibrium . they propose equilibriums that iteratively propose and refine natural-language guidelines .
Outcome: The proposed framework generates higher-quality and more balanced consensus . it finetunes diverse LLM architectures with negotiation data, reducing cultural distances by 95.53%.

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