2 citations · 3 across the 10 of their papers we have counts for
12 papers
WiseSpec: Requirements-Driven Agents for Code Generation
Zhao Tian
Code generation aims to automatically generate source code from task requirements and has attracted significant attention with the rapid advancement of large language models (LLMs)…
LLVM-Bench: Benchmarking and Advancing Large Language Models for LLVM Compiler Issue Resolution
Zhao Tian, Yingquan Zhao, Chenyao Suo +2
LLVM is a widely used compiler infrastructure whose scale and complexity make issue resolution labor-intensive and challenging. Although large language models (LLMs) have recently…
Large Language Models for Multi-Lingual Equivalent Mutant Detection: An Extended Empirical Study
Honglin Shu, Zhao Tian, Dong Wang +5
Mutation testing is a powerful technique for ensuring software quality. However, the presence of equivalent mutants introduces unnecessary costs and biases, limiting its practical…
"Refactoring Runaway": Understanding and Mitigating Tangled Refactorings in Coding Agents for Issue Resolution
Zhao Tian, Zifan Zhang, Tao Xiao +4
Recent advances in coding agents have shown remarkable progress in software issue resolution. In practice, real-world issues are typically bug fixes or feature requests in which hu…
Improving LLM Code Generation via Requirement-Aware Curriculum Reinforcement Learning
Shouyu Yin, Zhao Tian, Junjie Chen +1
Code generation, which aims to automatically generate source code from given programming requirements, has the potential to substantially improve software development efficiency. W…
REAgent: Requirement-Driven LLM Agents for Software Issue Resolution
Shiqi Kuang, Zhao Tian, Kaiwei Lin +5
Issue resolution aims to automatically generate patches from given issue descriptions and has attracted significant attention with the rapid advancement of large language models (L…
Advancing Language Models for Code-related Tasks
Zhao Tian
Recent advances in language models (LMs) have driven significant progress in various software engineering tasks. However, existing LMs still struggle with complex programming scena…
On the Effectiveness of Training Data Optimization for LLM-based Code Generation: An Empirical Study
Shiqi Kuang, Zhao Tian, Tao Xiao +2
Large language models (LLMs) have achieved remarkable progress in code generation, largely driven by the availability of high-quality code datasets for effective training. To furth…
Aligning Requirement for Large Language Model's Code Generation
Zhao Tian, Junjie Chen
Code generation refers to the automatic generation of source code based on a given programming specification, which has garnered significant attention particularly with the advance…
Trae Agent: An LLM-based Agent for Software Engineering with Test-time Scaling
Trae Research Team, Pengfei Gao, Zhao Tian +12
Software issue resolution is a critical challenge in software engineering and has garnered increasing attention in recent years. With the rapid advancement of large language models…
Large Language Models for Equivalent Mutant Detection: How Far Are We?
Zhao Tian, Honglin Shu, Dong Wang +3
Mutation testing is vital for ensuring software quality. However, the presence of equivalent mutants is known to introduce redundant cost and bias issues, hindering the effectivene…
Fixing Large Language Models' Specification Misunderstanding for Better Code Generation
Zhao Tian, Junjie Chen, Xiangyu Zhang
Code generation is to automatically generate source code conforming to a given programming specification, which has received extensive attention especially with the development of…