3 papers
cs.LG2026
Dr. Kernel: Reinforcement Learning Done Right for Triton Kernel Generations
Wei Liu, Jiawei Xu, Yingru Li +4
High-quality kernel is critical for scalable AI systems, and enabling LLMs to generate such code would advance AI development. However, training LLMs for this task requires suffici…
cs.LG2025
Sub-Scaling Laws: On the Role of Data Density and Training Strategies in LLMs
Zhengyu Chen, Siqi Wang, Teng Xiao +5
Traditional scaling laws in natural language processing suggest that increasing model size and training data enhances performance. However, recent studies reveal deviations, partic…
cs.CL2025
Does Learning Mathematical Problem-Solving Generalize to Broader Reasoning?
Ruochen Zhou, Minrui Xu, Shiqi Chen +5
There has been a growing interest in enhancing the mathematical problem-solving (MPS) capabilities of large language models. While the majority of research efforts concentrate on c…