5 citations · 8 across the 4 of their papers we have counts for
4 papers
Demystifying Deep Learning Compiler Frontend Bugs: An LLM-Aided Empirical Study
Xinyi Yuan, Wei Chen, Jinyi Liu +5
Deep learning compilers (DLCs) are designed to translate deep learning programs into optimized, hardware-specific code. Typically, DLC frontends translate programs into graph-based…
PATCH: Empowering Large Language Model with Programmer-Intent Guidance and Collaborative-Behavior Simulation for Automatic Bug Fixing
Yuwei Zhang, Zhi Jin, Ying Xing +5
Bug fixing holds significant importance in software development and maintenance. Recent research has made substantial strides in exploring the potential of large language models (L…
CITYWALK: Enhancing LLM-Based C++ Unit Test Generation via Project-Dependency Awareness and Language-Specific Knowledge
Yuwei Zhang, Qingyuan Lu, Kai Liu +6
Unit testing plays a pivotal role in the software development lifecycle, as it ensures code quality. However, writing high-quality unit tests remains a time-consuming task for deve…
STEAM: Simulating the InTeractive BEhavior of ProgrAMmers for Automatic Bug Fixing
Yuwei Zhang, Zhi Jin, Ying Xing +1
Bug fixing holds significant importance in software development and maintenance. Recent research has made notable progress in exploring the potential of large language models (LLMs…