activity
20242026
collaborators

7 papers

cs.SE2026

Diff Diffusion: Predicting Edit Paths with Diffusion Models for Efficient Code Editing

Xiaolong Xu, Hao Jiang, Bo Jiang +5

Diffusion large language models (dLLMs) are appealing for code generation because they can update many tokens in parallel, yet many are optimized for sequence synthesis rather than…

cs.AI2026

OptiCom : A Unified Framework for State-Conditioned Composition in LLM-Driven Optimization

Chenxing Wei, Sichen Liu, Lizhao Liu +6

Large language models (LLMs) are increasingly deployed to solve complex scientific and practical problems via iterative optimization. However, dynamically coordinating diverse sear…

cs.SE2026

KCoEvo: A Knowledge Graph Augmented Framework for Evolutionary Code Generation

Jiazhen Kang, Yuchen Lu, Chen Jiang +6

Code evolution is inevitable in modern software development. Changes to third-party APIs frequently break existing code and complicate maintenance, posing practical challenges for…

cs.LG2026

LFPO: Likelihood-Free Policy Optimization for Masked Diffusion Models

Chenxing Wei, Jiazhen Kang, Hong Wang +8

Reinforcement Learning with Verifiable Rewards (RLVR) has achieved remarkable success in improving autoregressive models, especially in domains requiring correctness like mathemati…

cs.CV2026

Fine-Grained Human Pose Editing Assessment via Layer-Selective MLLMs

Ningyu Sun, Zhaolin Cai, Zitong Xu +5

Text-guided human pose editing has gained significant traction in AIGC applications. However,it remains plagued by structural anomalies and generative artifacts. Existing evaluatio…

cs.SE2025

Evaluating Generated Commit Messages with Large Language Models

Qunhong Zeng, Yuxia Zhang, Zexiong Ma +5

Commit messages are essential in software development as they serve to document and explain code changes. Yet, their quality often falls short in practice, with studies showing sig…

cs.SE2024

ContextModule: Improving Code Completion via Repository-level Contextual Information

Zhanming Guan, Junlin Liu, Jierui Liu +7

Large Language Models (LLMs) have demonstrated impressive capabilities in code completion tasks, where they assist developers by predicting and generating new code in real-time. Ho…