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cs.LG2026
A Distribution-Matching Perspective on LLM Training Algorithms
Yanxing Huang, Bingzhang Yan, Zihan Tang +3
In this work, we propose a unified framework for training algorithms across different stages of modern large language model development, based on the perspective of distribution ma…
cs.LG2026
From Reasoning Chains to Verifiable Subproblems: Curriculum Reinforcement Learning Enables Credit Assignment for LLM Reasoning
Xitai Jiang, Zihan Tang, Wenze Lin +3
Reinforcement learning from verifiable rewards (RLVR) has shown strong promise for LLM reasoning, but outcome-based RLVR remains inefficient on hard problems because correct final-…