21 citations · 38 across the 10 of their papers we have counts for
10 papers
Towards the Generalizability of Leveraging ChatGPT in APR via Self-enhancing: An Empirical Study
Qingyuan Li, Chuanyi Li, Yaopeng Yang +3
Automated Program Repair (APR) increasingly relies on Large Language Models (LLMs). ChatGPT-enhanced APR uses techniques such as self-correction and autonomous agents to improve re…
RACER: Reinforced Agent Collaboration for Explainable Reasoning on Knowledge Graphs
Yuwei Lou, Hao Hu, Yuzhou Jiang +5
Large Language Models (LLMs) often suffer from hallucination and struggle with complex reasoning tasks requiring multi-hop domain knowledge. While integrating Knowledge Graphs (KGs…
UNICS: Multilingual Code Search via Unified Pseudocode and Contrastive Transfer Learning
Ye Fan, Jidong Ge, Chuanyi Li +2
While pre-trained models have achieved remarkable success in code search, their multilingual capabilities remain a major hurdle, plagued by data imbalance, cross-lingual semantic i…
Echo: Graph-Enhanced Retrieval and Execution Feedback for Issue Reproduction Test Generation
Zhiwei Fei, Yue Pan, Federica Sarro +4
Identifying the root cause of a bug remains difficult for many developers because bug reports often lack a bug reproducing test case that reliably triggers the failure. Manually wr…
DRF: LLM-AGENT Dynamic Reputation Filtering Framework
Yuwei Lou, Hao Hu, Shaocong Ma +4
With the evolution of generative AI, multi - agent systems leveraging large - language models(LLMs) have emerged as a powerful tool for complex tasks. However, these systems face c…
Refactoring Bug-Inducing: Improving Defect Prediction with Code Change Tactics Analysis
Feifei Niu, Junqian Shao, Christoph Mayr-Dorn +5
Just-in-time defect prediction (JIT-DP) aims to predict the likelihood of code changes resulting in software defects at an early stage. Although code change metrics and semantic fe…
InternLM-Law: An Open Source Chinese Legal Large Language Model
Zhiwei Fei, Songyang Zhang, Xiaoyu Shen +9
While large language models (LLMs) have showcased impressive capabilities, they struggle with addressing legal queries due to the intricate complexities and specialized expertise r…
FT2Ra: A Fine-Tuning-Inspired Approach to Retrieval-Augmented Code Completion
Qi Guo, Xiaohong Li, Xiaofei Xie +6
The rise of code pre-trained models has significantly enhanced various coding tasks, such as code completion, and tools like GitHub Copilot. However, the substantial size of these…
A Comprehensive Evaluation of Parameter-Efficient Fine-Tuning on Software Engineering Tasks
Wentao Zou, Qi Li, Jidong Ge +4
Pre-trained models (PTMs) have achieved great success in various Software Engineering (SE) downstream tasks following the ``pre-train then fine-tune'' paradigm. As fully fine-tunin…
LawBench: Benchmarking Legal Knowledge of Large Language Models
Zhiwei Fei, Xiaoyu Shen, Dawei Zhu +6
Large language models (LLMs) have demonstrated strong capabilities in various aspects. However, when applying them to the highly specialized, safe-critical legal domain, it is uncl…