HF Daily Papers
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Spectral Rewiring for Exploration, Purification, and Model Merging
Reinforcement learning has become a standard post-training recipe for large language models, but dense full-parameter updates create two deployment-relevant bottlenecks: suppressed reasoning performance, often reflected by premature saturation of test-time scaling, and interference when consolidatin