activity
20222026
most citedEditSum: A Retrieve-and-Edit Framework for Source Code Summarization

59 citations · 145 across the 33 of their papers we have counts for

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Showing 2024Show all

9 papers · 1 filter

cs.CL2024

Generating Equivalent Representations of Code By A Self-Reflection Approach

Jia Li, Ge Li, Lecheng Wang +2

Equivalent Representations (ERs) of code are textual representations that preserve the same semantics as the code itself, e.g., natural language comments and pseudocode. ERs play a…

cs.SE2024

Showing LLM-Generated Code Selectively Based on Confidence of LLMs

Jia Li, Yuqi Zhu, Yongmin Li +2

Large Language Models (LLMs) have shown impressive abilities in code generation, but they may generate erroneous programs. Reading a program takes ten times longer than writing it.…

cs.SE2024★ 1 cited

Sifting through the Chaff: On Utilizing Execution Feedback for Ranking the Generated Code Candidates

Zhihong Sun, Yao Wan, Jia Li +4

Large Language Models (LLMs), such as GPT-4, StarCoder, and CodeLlama, are transforming the way developers approach programming by automatically generating code based on given natu…

cs.SE2024

M2CVD: Enhancing Vulnerability Semantic through Multi-Model Collaboration for Code Vulnerability Detection

Ziliang Wang, Ge Li, Jia Li +3

Large Language Models (LLMs) have strong capabilities in code comprehension, but fine-tuning costs and semantic alignment issues limit their project-specific optimization; converse…

cs.SE2024

Line-level Semantic Structure Learning for Code Vulnerability Detection

Ziliang Wang, Ge Li, Jia Li +3

Unlike the flow structure of natural languages, programming languages have an inherent rigidity in structure and grammar.However, existing detection methods based on pre-trained mo…

cs.SE2024★ 3 cited

Exploring and Unleashing the Power of Large Language Models in Automated Code Translation

Zhen Yang, Fang Liu, Zhongxing Yu +7

Code translation tools (transpilers) are developed for automatic source-to-source translation. Although learning-based transpilers have shown impressive enhancement against rule-ba…

cs.CL2024★ 1 cited

A Comprehensive Evaluation on Event Reasoning of Large Language Models

Zhengwei Tao, Zhi Jin, Yifan Zhang +7

Event reasoning is a fundamental ability that underlies many applications. It requires event schema knowledge to perform global reasoning and needs to deal with the diversity of th…

cs.SE2024★ 4 cited

CodeAgent: Enhancing Code Generation with Tool-Integrated Agent Systems for Real-World Repo-level Coding Challenges

Kechi Zhang, Jia Li, Ge Li +2

Large Language Models (LLMs) have shown promise in automated code generation but typically excel only in simpler tasks such as generating standalone code units. Real-world software…

cs.SE2024★ 3 cited

DevEval: Evaluating Code Generation in Practical Software Projects

Jia Li, Ge Li, Yunfei Zhao +14

How to evaluate Large Language Models (LLMs) in code generation is an open question. Many benchmarks have been proposed but are inconsistent with practical software projects, e.g.,…