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cs.LG2026
Flexible Entropy Control in RLVR with a Gradient-Preserving Perspective
Kun Chen, Peng Shi, Fanfan Liu +4
Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a critical method for enhancing the reasoning capabilities of Large Language Models (LLMs). However, continuous…
cs.LG2026
Metis-SPECS: Decoupling Multimodal Learning via Self-distilled Preference-based Cold Start
Kun Chen, Peng Shi, Haibo Qiu +4
Reinforcement learning (RL) with verifiable rewards has recently catalyzed a wave of "MLLM-r1" approaches that bring RL to vision language models. Most representative paradigms beg…