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cs.AI2026
Toward a Dynamic Stackelberg Game-Theoretic Framework for Agentic AI Defense Against LLM Jailbreaking
Zhengye Han, Quanyan Zhu
This paper proposes a game theoretic framework that models the interaction between prompt engineers and large language models (LLMs) as a two player extensive form game coupled wit…
cs.AI2025
GroundedPRM: Tree-Guided and Fidelity-Aware Process Reward Modeling for Step-Level Reasoning
Yao Zhang, Yu Wu, Haowei Zhang +6
Process Reward Models (PRMs) aim to improve multi-step reasoning in Large Language Models (LLMs) by supervising intermediate steps and identifying errors. However, building effecti…
cs.AI2024
WebPilot: A Versatile and Autonomous Multi-Agent System for Web Task Execution with Strategic Exploration
Yao Zhang, Zijian Ma, Yunpu Ma +3
LLM-based autonomous agents often fail to execute complex web tasks that require dynamic interaction due to the inherent uncertainty and complexity of these environments. Existing…