4 citations · 7 across the 9 of their papers we have counts for
4 papers · 1 filter
DSEffi-Bench: Demystifying Large Language Models' Capability in Efficient Data Science Code Generation
Zhihao Gong, Junzhe Yu, Dong Huang +3
Current data science (DS) code generation benchmarks equate correctness with quality, overlooking execution time differences that span orders of magnitude between correct solutions…
WarmTuner: Program-Specific Warm Starts for Compiler Autotuning via Offline-to-Online Reinforcement Learning
Tianlu Qiao, Mingxuan Zhu, Zeyu Sun +1
Compilers are fundamental software tools that translate high-level programs into machine code. Modern compilers expose hundreds of optimizations, each turned on or off through an o…
TestDecision: Sequential Test Suite Generation via Greedy Optimization and Reinforcement Learning
Guoqing Wang, Chengran Yang, Xiaoxuan Zhou +4
With the rapid evolution of LLMs, automated software testing is witnessing a paradigm shift. While proprietary models like GPT-4o demonstrate impressive capabilities, their high de…
Search-Induced Issues in Web-Augmented LLM Code Generation: Detecting and Repairing Error-Inducing Pages
Guoqing Wang, Zeyu Sun, Xiaofei Xie +4
Web-augmented large language models (LLMs) offer promising capabilities for automatic code generation. However, integrating live web search exposes models to unreliable or maliciou…