activity
20242026
most citedLearning Project-wise Subsequent Code Edits via Interleaving Neural-based Induction and Tool-based Deduction

1 citations · 1 across the 3 of their papers we have counts for

collaborators

7 papers

cs.SE2026

Generalizing Test Cases for Comprehensive Test Scenario Coverage

Binhang Qi, Yun Lin, Xinyi Weng +4

Test cases are essential for software development and maintenance. In practice, developers derive multiple test cases from an implicit pattern based on their understanding of requi…

cs.SE20261 cited

Learning Project-wise Subsequent Code Edits via Interleaving Neural-based Induction and Tool-based Deduction

Chenyan Liu, Yun Lin, Yuhuan Huang +5

In industrial and open-source software engineering tasks, developers often perform project-wise code editing tasks, including feature enhancement, refactoring, and bug fixing, wher…

cs.SE2026

EditFlow: Benchmarking and Optimizing Code Edit Recommendation Systems via Reconstruction of Developer Flows

Chenyan Liu, Yun Lin, Jiaxin Chang +5

Large language models (LLMs) for code editing have achieved remarkable progress, yet recent empirical studies reveal a fundamental disconnect between technical accuracy and develop…

cs.LG2025

NeMo: A Neuron-Level Modularizing-While-Training Approach for Decomposing DNN Models

Xiaohan Bi, Binhang Qi, Hailong Sun +3

With the growing incorporation of deep neural network (DNN) models into modern software systems, the prohibitive construction costs have become a significant challenge. Model reuse…

cs.LG2025

CABS: Conflict-Aware and Balanced Sparsification for Enhancing Model Merging

Zongzhen Yang, Binhang Qi, Hailong Sun +3

Model merging based on task vectors, i.e., the parameter differences between fine-tuned models and a shared base model, provides an efficient way to integrate multiple task-specifi…

cs.LG2025

Clustering Properties of Self-Supervised Learning

Xi Weng, Jianing An, Xudong Ma +5

Self-supervised learning (SSL) methods via joint embedding architectures have proven remarkably effective at capturing semantically rich representations with strong clustering prop…