Berkeley Paper: RL Reweights Rather Than Expands LLM Reasoning Boundary

A UC Berkeley paper on Qwen and Gemma models finds that reinforcement learning does not expand LLM reasoning boundaries but instead reweights existing strategies: Pass@1 improves while Pass@N may drop, with scaling laws also provided.

2026-10-27 ~ 2026-10-28 · 3 related posts

• UC Berkeley paper: RL reweights LLM reasoning strategies rather than expanding them — burny_tech · 2026-10-27
• Does RL Expand LLM Reasoning or Just Reweight It? New Study Offers Theory and Scaling Laws — burny_tech · 2026-10-28

1 near-duplicate retellings: burny_tech