Author

Hang Xu

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Jul 2026

Harness Engineering for LLM-Driven GPU Kernel Generation

The Agent-Ass kernels outperform the Full-Agent artifacts across the evaluated definitions, indicating that expert-provided optimization directions, high-quality references, and workload context remain critical for reliable AI-driven kernel optimization.

Yue Shui, Chenyu Ma, Hang Xu et al. · arXiv.org · 1 citation

Preprint Aug 2026

CVPO: Enhancing LLM Reinforcement Learning Reasoning via Value-Variance Adaptation and Dynamic Curriculum Learning

This work proposes CVPO - Curriculum-guided Value-Variance Policy Optimization, a dynamic curriculum weighting method that adapts to question difficulty that achieves better performance and stronger exploration, enabling more accurate and robust reasoning in language models across various math tasks.

Ziqi Jia, Yalu Ouyang, Bo Pang et al. · 0 citations