15 citations · 21 across the 11 of their papers we have counts for
11 papers
Chiseling Out Efficiency: Structured Skeleton Supervision for Efficient Code Generation
Yu Yu, Zhihong Sun, Jia Li +8
Large Language Models (LLMs) are capable of generating syntactically correct and functionally complete programs, greatly streamlining software development. However, recent studies…
MAS-Algorithm: A Workflow for Solving Algorithmic Programming Problems with a Multi-Agent System
Yuliang Xu, Xiang Xu, Yao Wan +2
Algorithmic problem solving serves as a rigorous testbed for evaluating structured reasoning in AI coding systems, as it directly reflects a model's ability to perform structured r…
Ensembling Large Language Models for Code Vulnerability Detection: An Empirical Evaluation
Zhihong Sun, Jia Li, Yao Wan +7
Code vulnerability detection is crucial for ensuring the security and reliability of modern software systems. Recently, Large Language Models (LLMs) have shown promising capabiliti…
Scrub It Out! Erasing Sensitive Memorization in Code Language Models via Machine Unlearning
Zhaoyang Chu, Yao Wan, Zhikun Zhang +7
While Code Language Models (CLMs) have demonstrated superior performance in software engineering tasks such as code generation and summarization, recent empirical studies reveal a…
nvAgent: Automated Data Visualization from Natural Language via Collaborative Agent Workflow
Geliang Ouyang, Jingyao Chen, Zhihe Nie +4
Natural Language to Visualization (NL2Vis) seeks to convert natural-language descriptions into visual representations of given tables, empowering users to derive insights from larg…
Can Large Language Models Understand Intermediate Representations in Compilers?
Hailong Jiang, Jianfeng Zhu, Yao Wan +4
Intermediate Representations (IRs) play a critical role in compiler design and program analysis, yet their comprehension by Large Language Models (LLMs) remains underexplored. In t…
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…
WebCode2M: A Real-World Dataset for Code Generation from Webpage Designs
Yi Gui, Zhen Li, Yao Wan +10
Automatically generating webpage code from webpage designs can significantly reduce the workload of front-end developers, and recent Multimodal Large Language Models (MLLMs) have s…
Enhancing Code Generation Performance of Smaller Models by Distilling the Reasoning Ability of LLMs
Zhihong Sun, Chen Lyu, Bolun Li +4
Large Language Models (LLMs) have recently made significant advances in code generation through the 'Chain-of-Thought' prompting technique. This technique empowers the model to aut…
IRCoCo: Immediate Rewards-Guided Deep Reinforcement Learning for Code Completion
Bolun Li, Zhihong Sun, Tao Huang +5
Code completion aims to enhance programming productivity by predicting potential code based on the current programming context. Recently, pretrained language models (LMs) have beco…
NL2Formula: Generating Spreadsheet Formulas from Natural Language Queries
Wei Zhao, Zhitao Hou, Siyuan Wu +6
Writing formulas on spreadsheets, such as Microsoft Excel and Google Sheets, is a widespread practice among users performing data analysis. However, crafting formulas on spreadshee…