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cs.LG2026
Climbing the Hill: Prompt Injection Red-Teaming Against Frontier Models with Curriculum Reinforcement Learning
Chenlong Yin, Xiaolong Jin, Wei Zou +2
Prompt injection is a leading security risk for LLMs and LLM-based applications such as agents. State-of-the-art red-teaming methods for prompt injection leverage reinforcement lea…
cs.LG2026
PISmith: Reinforcement Learning-based Red Teaming for Prompt Injection Defenses
Chenlong Yin, Runpeng Geng, Yanting Wang +1
Prompt injection poses serious security risks to real-world LLM applications, particularly autonomous agents. Although many defenses have been proposed, their robustness against ad…
cs.LG2025
The Reasoning Trap: How Enhancing LLM Reasoning Amplifies Tool Hallucination
Chenlong Yin, Zeyang Sha, Shiwen Cui +2
Enhancing the reasoning capabilities of Large Language Models (LLMs) is a key strategy for building Agents that "think then act." However, recent observations, like OpenAI's o3, su…