KernelGenBench is presented, the first unified multi-source and multi-chip infrastructure for evaluating LLM- and agent-generated Triton kernels and establishes operator source, hardware platform, and agentic scaffold as distinct dimensions of kernel-generation capability, and shows that success in a familiar source-ha...
Pei-Yu Zang, Jian-Hang Tao, Jia-Ling Zhang et al.· 0 citations
It is shown that agent-based methods consistently outperform pure LLM sampling methods, while cuBLAS operators are the most challenging across all methods, and a unified benchmark for systematically evaluating LLM-and agent-generated Triton kernels across diverse operator sources and heterogeneous hardware platforms is...
This work presents DREAM (Developing Recommender Engine with Agentic Methods), an autonomous optimization control architecture that adds a perception-aware, orchestrable, and auditable policy layer atop existing pipelines without replacing them, supporting agentic meta-control as a viable paradigm for industrial recomm...
Bin Zhang, Bo-Wen Zheng, Chao Yi et al.· 0 citations
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