Hongyu Zhang

On the Evaluation of Commit Message Generation Models: An Experimental Study

2021

Commit messages are natural language descriptions of code changes, which are important for program understanding and maintenance. However, writing commit messages manually is time-consuming and laborious, especially when the code is updated frequently. Various approaches …

Patching Weak Convolutional Neural Network Models through Modularization and Composition

2022

Despite great success in many applications, deep neural networks are not always robust in practice. For instance, a convolutional neuron network (CNN) model for classification tasks often performs unsatisfactorily in classifying some particular classes of …

Modularizing while Training: A New Paradigm for Modularizing DNN Models

2023 · arXiv (Cornell University)

Deep neural network (DNN) models have become increasingly crucial components in intelligent software systems. However, training a DNN model is typically expensive in terms of both time and money. To address this issue, researchers have …

FedHCDR: Federated Cross-Domain Recommendation with Hypergraph Signal Decoupling

2024 · arXiv (Cornell University)

In recent years, Cross-Domain Recommendation (CDR) has drawn significant attention, which utilizes user data from multiple domains to enhance the recommendation performance. However, current CDR methods require sharing user data across domains, thereby violating the …

FedDCSR: Federated Cross-domain Sequential Recommendation via Disentangled Representation Learning

2024 · Society for Industrial and Applied Mathematics eBooks

Cross-domain Sequential Recommendation (CSR) which leverages user sequence data from multiple domains has received extensive attention in recent years. However, the existing CSR methods require sharing origin user data across domains, which violates the General …

HumanEvo: An Evolution-Aware Benchmark for More Realistic Evaluation of Repository-Level Code Generation

2025

To evaluate the repository-level code generation capabilities of Large Language Models (LLMs) in complex real-world software development scenarios, many evaluation methods have been developed. These methods typically leverage contextual code from the latest version of …

Retrieval-based neural source code summarization

2020

Source code summarization aims to automatically generate concise summaries of source code in natural language texts, in order to help developers better understand and maintain source code. Traditional work generates a source code summary by …