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Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning

arXiv — cs.LG•Friday, November 14, 2025 at 5:00:00 AM
PositiveArtificial Intelligence
The findings from the article on high-entropy minority tokens in RLVR resonate with ongoing research in visual reasoning and mathematical reasoning within LLMs. For instance, the study on PROPA highlights the challenges faced by Vision-Language Models (VLMs) in complex visual reasoning, where multi-step dependencies can lead to errors. Similarly, the work on improving LLMs' critique on math reasoning through perplexity-aware reinforcement learning emphasizes the need for effective supervision in reasoning processes. Together, these studies underscore the importance of refining methodologies in AI to enhance reasoning capabilities across various domains.
— via World Pulse Now AI Editorial System
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