5 papers
From Tokens to Regions: CUDA-Sensitive Instruction Tuning for GPU Kernel Generation
Wentao Chen, Jiace Zhu, Xing Zhe Chai +4
High-performance CUDA kernels are essential for scalable AI systems, while Large Language Models (LLMs) still struggle to generate correct kernels due to strict and implicit execut…
CUDA-LLM: LLMs Can Write Efficient CUDA Kernels
Wentao Chen, Jiace Zhu, Qi Fan +2
Large Language Models (LLMs) have demonstrated strong capabilities in general-purpose code generation. However, generating the code which is deeply hardware-specific, architecture-…
Evaluating Harmful Memorization in LLM Code Generation
Lizhe Zhang, Wentao Chen, Li Zhong +3
Assessing memorization in LLM code generation is challenging because code reuse is not inherently harmful. Correct programs often share APIs, templates, and algorithmic idioms, so…
The Rise and Down of Babel Tower: Investigating the Evolution Process of Multilingual Code Large Language Model
Jiawei Chen, Wentao Chen, Jing Su +6
Large language models (LLMs) have shown significant multilingual capabilities. However, the mechanisms underlying the development of these capabilities during pre-training are not…
Tree Search-Based Evolutionary Bandits for Protein Sequence Optimization
Jiahao Qiu, Hui Yuan, Jinghong Zhang +3
While modern biotechnologies allow synthesizing new proteins and function measurements at scale, efficiently exploring a protein sequence space and engineering it remains a dauntin…