most citedReasoning Efficiently Through Adaptive Chain-of-Thought Compression: A Self-Optimizing Framework

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.SE2026

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…

cs.SE20261 cited

Reasoning Efficiently Through Adaptive Chain-of-Thought Compression: A Self-Optimizing Framework

Kerui Huang, Shuhan Liu, Xing Hu +3

Chain-of-Thought (CoT) reasoning enhances Large Language Models (LLMs) by prompting intermediate steps, improving accuracy and robustness in arithmetic, logic, and commonsense task…

cs.SE2026

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…

cs.SE2026

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…

cs.SE2025

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…