works on

From the 1 of 4 linked papers with an AI index.

collaborators

5 papers

cs.SE2026

MultiFixer: A Coordinator-Proposer Based Multi-Agent Framework For Fixing Multi-Hunk Bugs

Haichuan Hu, Chunrong Fang, Ye Shang +5

The paper introduces MultiFixer, a multi-agent framework that uses a Coordinator‑Proposer architecture to coordinate large language model generated patches for fixing bugs that spa…

cs.SE2026

EvoRepair: Enhancing Vulnerability Repair Agents Through Experience-Based Self-Evolution

Haichuan Hu, Guoqing Xie, Quanjun Zhang +5

Large Language Models (LLMs) have shown promise for automated vulnerability repair (AVR), but they still face several limitations, including the lack of intra-vulnerability experie…

cs.SE2026

CL4SE: Benchmarking Context Learning on Software Engineering

Haichuan Hu, Quanjun Zhang, Ye Shang +4

Context engineering has emerged as a pivotal paradigm for unlocking the potential of Large Language Models (LLMs) in Software Engineering (SE) tasks, enabling performance gains at…

cs.CL2025

Efficient Prompt Compression with Evaluator Heads for Long-Context Transformer Inference

Weizhi Fei, Xueyan Niu, Guoqing Xie +3

Although applications involving long-context inputs are crucial for the effective utilization of large language models (LLMs), they also result in increased computational costs and…

cs.CL2024

Retrieval Meets Reasoning: Dynamic In-Context Editing for Long-Text Understanding

Weizhi Fei, Xueyan Niu, Guoqing Xie +4

Current Large Language Models (LLMs) face inherent limitations due to their pre-defined context lengths, which impede their capacity for multi-hop reasoning within extensive textua…