8 citations · 8 across the 7 of their papers we have counts for
8 papers
RepoNav: From Snippet Retrieval to File-Centered Repository Navigation for Code Agents
Hongzheng Chai, Jiakun Li, Hongyue Yu +1
Solving repository-level code tasks requires LLM-based agents to use code search tools to navigate large codebases and identify a small set of relevant files and functions. However…
TDD-Agent: Test-Driven Reasoning for Code Generation
Hongyue Yu, Kefan Li, Jiakun Li +4
Large Language Models (LLMs) have achieved remarkable progress in code generation, yet ensuring correctness in complex, repository-level tasks remains challenging. Existing approac…
Escaping the Self-Repair Trap: Improving Test Oracle Generation via Dual-Context Awareness
Kefan Li, Hongyue Yu, Yuan Yuan
Large Language Models (LLMs) have shown strong potential for regression-oracle completion, where a test prefix is given and the current program version is treated as expected behav…
DynaSchedBench: Calibrated Dynamic Scheduling Benchmarks and Observability Paradox in LLM-based Scheduling Agents
Shijie Cao, Yuan Yuan, Jing Liu
Progress in neural combinatorial optimization for Dynamic Flexible Job Shop Scheduling Problem (DFJSP) is currently hindered by a methodological tension: static benchmarks encourag…
MemTrace: Tracing and Attributing Errors in Large Language Model Memory Systems
Xinle Deng, Ruobin Zhong, Hujin Peng +15
Memory is essential for enabling large language models to support long-horizon reasoning, yet existing memory systems remain unreliable and difficult to debug. Tracing memory's dyn…
CoCoEvo: Co-Evolution of Programs and Test Cases to Enhance Code Generation
Kefan Li, Yuan Yuan, Hongyue Yu +2
Large Language Models (LLMs) have shown remarkable performance in automated code generation. However, existing approaches often rely heavily on pre-defined test cases, which become…