9 citations · 10 across the 7 of their papers we have counts for
7 papers
RealisticTritonBench: A Benchmark for Triton-Kernel Generation in Real-World AI Frameworks
Jinjun Huang, Zhongzhen Wen, Tongtong Xu +3
In modern AI frameworks, GPU kernels are key to overall system performance. Combining usability, portability, and near-handwritten CUDA performance, Triton is widely adopted for im…
LLM-Powered Silent Bug Fuzzing in Deep Learning Libraries via Versatile and Controlled Bug Transfer
Kunpeng Zhang, Dongwei Xiao, Daoyuan Wu +5
Deep learning (DL) libraries are widely used in critical applications, where even subtle silent bugs can lead to serious consequences. While existing DL fuzzing techniques have mad…
DepRadar: Agentic Coordination for Context Aware Defect Impact Analysis in Deep Learning Libraries
Yi Gao, Xing Hu, Tongtong Xu +3
Deep learning libraries like Transformers and Megatron are now widely adopted in modern AI programs. However, when these libraries introduce defects, ranging from silent computatio…
Actionable Warning Is Not Enough: Recommending Valid Actionable Warnings with Weak Supervision
Zhipeng Xue, Zhipeng Gao, Tongtong Xu +3
The use of static analysis tools has gained increasing popularity among developers in the last few years. However, the widespread adoption of static analysis tools is hindered by t…
SEER: Self-Enhancing Chain-of-Thought Compression for Reasoning Models
Kerui Huang, Shuhan Liu, Xing Hu +3
Chain-of-Thought (CoT) prompting can substantially improve the reasoning ability of large language models (LLMs), but it often comes with high inference cost due to long and poorly…
Exploiting Library Vulnerability via Migration Based Automating Test Generation
Zirui Chen, Xing Hu, Xin Xia +4
In software development, developers extensively utilize third-party libraries to avoid implementing existing functionalities. When a new third-party library vulnerability is disclo…
Practical Program Repair via Preference-based Ensemble Strategy
Wenkang Zhong, Chuanyi Li, Kui Liu +5
To date, over 40 Automated Program Repair (APR) tools have been designed with varying bug-fixing strategies, which have been demonstrated to have complementary performance in terms…