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cs.AI2026
RL-PLUS: Countering Capability Boundary Collapse of LLMs in Reinforcement Learning with Hybrid-policy Optimization
Yihong Dong, Xue Jiang, Yongding Tao +11
Reinforcement Learning with Verifiable Reward (RLVR) has significantly advanced the complex reasoning abilities of Large Language Models (LLMs). However, it struggles to break thro…
cs.AI2026
Two Heads are Better than One: Distilling Large Language Model Features Into Small Models with Feature Decomposition and Mixture
Tianhao Fu, Xinxin Xu, Weichen Xu +6
Market making (MM) through Reinforcement Learning (RL) has attracted significant attention in financial trading. With the development of Large Language Models (LLMs), more and more…