Sharpening Tax : un papier mesure la perte de couverture des solutions après le post-entraînement par RL

An emerging hypothesis about reinforcement learning (RL) post-training of large language models (LLMs) is that it merely sharpens existing behaviors of a base model, improving single-shot accuracy at the cost of solution coverage.