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Xinbo Xu

2 accepted papers

2026

Think Fast and Slow: Step-Level Cognitive Depth Adaptation for LLM Agents

ICML 2026poster

Large language models (LLMs) are increasingly deployed as autonomous agents for multi-turn decision-making tasks. However, current agents typically rely on fixed cognitive patterns: non-thinking models generate immediate responses, while thinking models engage in deep reasoning uniformly. This rigid…

Cited by 0SourceScholar
2024

Safe RLHF: Safe Reinforcement Learning from Human Feedback

ICLR 2024spotlight

With the development of large language models (LLMs), striking a balance between the performance and safety of AI systems has never been more critical. However, the inherent tension between the objectives of helpfulness and harmlessness presents a significant challenge during LLM training. To addres…