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cs.CL2026
Rethinking RL for LLM Reasoning: It's Sparse Policy Selection, Not Capability Learning
Ömer Faruk Akgül, Rajgopal Kannan, Willie Neiswanger +1
Reinforcement learning has become the standard for improving reasoning in large language models, yet evidence increasingly suggests that RL does not teach new strategies; it redist…
cs.CL2025★ 1 cited
Estimating LLM Consistency: A User Baseline vs Surrogate Metrics
Xiaoyuan Wu, Weiran Lin, Omer Akgul +1
Large language models (LLMs) are prone to hallucinations and sensitive to prompt perturbations, often resulting in inconsistent or unreliable generated text. Different methods have…