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cs.LG2026
Making LLMs Optimize Multi-Scenario CUDA Kernels Like Experts
Yuxuan Han, Meng-Hao Guo, Zhengning Liu +2
Optimizing GPU kernels manually is a challenging and time-consuming task. With the rapid development of LLMs, automated GPU kernel optimization is gradually becoming a tangible rea…
cs.LG2025
DEER: Draft with Diffusion, Verify with Autoregressive Models
Zicong Cheng, Guo-Wei Yang, Jia Li +3
Efficiency, as a critical practical challenge for LLM-driven agentic and reasoning systems, is increasingly constrained by the inherent latency of autoregressive (AR) decoding. Spe…