14 papers
PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents
Tianyue Jiang, Yanlin Wang, Xin He +7
While Large Language Models have greatly advanced automated issue resolution, existing agent-based methods exhibit a fundamental limitation in their insufficient exploration of rep…
AlignCoder: Aligning Retrieval with Target Intent for Repository-Level Code Completion
Tianyue Jiang, Yanli Wang, Yanlin Wang +5
Repository-level code completion remains a challenging task for existing code large language models (code LLMs) due to their limited understanding of repository-specific context an…
Yet Even Less Is Even Better For Agentic, Reasoning, and Coding LLMs
CodeArts Model Team, Yang Ye, Jingyuan Tan +24
Training effective software engineering agents requires large volumes of task-specific trajectories, incurring substantial data construction costs. Inspired by the "Less-Is-More" h…
Towards an Understanding of Context Utilization in Code Intelligence
Yanlin Wang, Kefeng Duan, Dewu Zheng +9
Code intelligence is an emerging domain in software engineering, aiming to improve the effectiveness and efficiency of various code-related tasks. Recent research suggests that inc…
DRAINCODE: Stealthy Energy Consumption Attacks on Retrieval-Augmented Code Generation via Context Poisoning
Yanlin Wang, Jiadong Wu, Tianyue Jiang +7
Large language models (LLMs) have demonstrated impressive capabilities in code generation by leveraging retrieval-augmented generation (RAG) methods. However, the computational cos…
ShortCoder: Knowledge-Augmented Syntax Optimization for Token-Efficient Code Generation
Sicong Liu, Yanxian Huang, Mingwei Liu +6
Code generation tasks aim to automate the conversion of user requirements into executable code, significantly reducing manual development efforts and enhancing software productivit…