12 citations · 12 across the 3 of their papers we have counts for
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cs.LG2026
Compaction-Aware Reinforcement Learning For Ascend Triton Kernel Generation
Chuansai Zhou, Yanlin Liu, Bingning Huang +7
Automatically generating high-performance kernels with LLM-based agents promises substantial gains in development efficiency, but two obstacles remain. First, while increasing mult…
cs.LG2026
MoE Proxy Models for Low-Cost Failure Reproduction and Diagnosis in LLM RL Post-Training
Yikai Wang, Chuansai Zhou, Yuhang Zhou +10
Reinforcement learning (RL) post-training of large language models (LLMs) is computationally intensive and involves complex system pipelines with substantial debugging overhead. In…