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cs.AI2026
The Refusal--Compliance Tradeoff: A Large-Scale Safety Behavior Audit of Large Language Models
Alif Al Hasan, Sumon Biswas
Refusal rates are a poor proxy for LLM safety, i.e., a model may over-refuse benign prompts while still complying with harmful ones. We audit both failure modes across 21 open-weig…
cs.AI2026
Plan Then Action:High-Level Planning Guidance Reinforcement Learning for LLM Reasoning
Zhihao Dou, Qinjian Zhao, Zhongwei Wan +10
Large language models (LLMs) demonstrate strong reasoning abilities via Chain-of-Thought (CoT), but their token-level generation encourages local decisions and lacks global plannin…
cs.AI2026
CoRe-Code: Collaborative Reinforcement Learning for Code Generation
Zhihao Dou, Qinjian Zhao, Zhongwei Wan +2
Large language models (LLMs) have achieved strong performance in code generation, but most methods rely on autoregressive decoding without global planning, often leading to locally…