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cs.LG2026
Distilled Reinforcement Learning for LLM Post-training
Chen Wang, Zhaochun Li, Jionghao Bai +4
Large language model (LLM) post-training is essential for improving reasoning, adaptation, and alignment. Existing methods mainly follow two paradigms: reinforcement learning (RL)…
cs.LG2020★ 3 cited
Zero-Shot Compositional Policy Learning via Language Grounding
Tianshi Cao, Jingkang Wang, Yining Zhang +1
Despite recent breakthroughs in reinforcement learning (RL) and imitation learning (IL), existing algorithms fail to generalize beyond the training environments. In reality, humans…