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Deng Pan

2 papers indexed

arxivcs.LGcs.AI2026-07-08

Predicting LLM Safety Before Release by Simulating Deployment

Marcus Williams, Hannah Sheahan, Cameron Raymond, Tomek Korbak, Deng Pan, Peilin Yang, et al.

Pre-deployment safety evaluations aim to inform the downstream risks of releasing a new AI model. Yet most evaluations provide limited evidence about how often undesired model behavior will occur in deployment: they generally have insufficient coverage, are unrepresentative, and…

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arxivcs.AI2026-07-08

CANN Bench: Benchmarking Agent Generated Kernels against Real NPU and Algorithmic Limits

Xue-Jian Gao, Deng Pan, Yueming Su, Jiasheng Li, Bin Du, Fengming Zhu, et al.

AI agents are now capable of writing, compiling, and iteratively optimizing low-level operator kernels on different hardware platforms. Existing benchmarks, however, focus almost exclusively on CUDA and Triton, leaving hardware ecosystems with less-exposed programming models with…

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