26 citations · 107 across the 14 of their papers we have counts for
15 papers
PassSum: Leveraging Paths of Abstract Syntax Trees and Self-Supervision for Code Summarization
Changan Niu, Chuanyi Li, Vincent Ng +3
Code summarization is to provide a high-level comment for a code snippet that typically describes the function and intent of the given code. Recent years have seen the successful a…
An Extensive Replication Study of the ABLoTS Approach for Bug Localization
Feifei Niu, Enshuo Zhang, Christoph Mayr-Dorn +5
Bug localization is the task of recommending source code locations (typically files) that contain the cause of a bug and hence need to be changed to fix the bug. Along these lines,…
Domain Adaptive Code Completion via Language Models and Decoupled Domain Databases
Ze Tang, Jidong Ge, Shangqing Liu +4
Large Language Models (LLMs) have demonstrated remarkable performance in code completion. However, due to the lack of domain-specific knowledge, they may not be optimal in completi…
Practical Program Repair via Preference-based Ensemble Strategy
Wenkang Zhong, Chuanyi Li, Kui Liu +5
To date, over 40 Automated Program Repair (APR) tools have been designed with varying bug-fixing strategies, which have been demonstrated to have complementary performance in terms…
Judicial Intelligent Assistant System: Extracting Events from Divorce Cases to Detect Disputes for the Judge
Yuan Zhang, Chuanyi Li, Yu Sheng +2
In formal procedure of civil cases, the textual materials provided by different parties describe the development process of the cases. It is a difficult but necessary task to extra…
An Empirical Comparison of Pre-Trained Models of Source Code
Changan Niu, Chuanyi Li, Vincent Ng +3
While a large number of pre-trained models of source code have been successfully developed and applied to a variety of software engineering (SE) tasks in recent years, our understa…
Learning the Relation between Similarity Loss and Clustering Loss in Self-Supervised Learning
Jidong Ge, Yuxiang Liu, Jie Gui +5
Self-supervised learning enables networks to learn discriminative features from massive data itself. Most state-of-the-art methods maximize the similarity between two augmentations…
MDIA: A Benchmark for Multilingual Dialogue Generation in 46 Languages
Qingyu Zhang, Xiaoyu Shen, Ernie Chang +2
Owing to the lack of corpora for low-resource languages, current works on dialogue generation have mainly focused on English. In this paper, we present mDIA, the first large-scale…
Neural Program Repair: Systems, Challenges and Solutions
Wenkang Zhong, Chuanyi Li, Jidong Ge +1
Automated Program Repair (APR) aims to automatically fix bugs in the source code. Recently, as advances in Deep Learning (DL) field, there is a rise of Neural Program Repair (NPR)…
SPT-Code: Sequence-to-Sequence Pre-Training for Learning Source Code Representations
Changan Niu, Chuanyi Li, Vincent Ng +3
Recent years have seen the successful application of large pre-trained models to code representation learning, resulting in substantial improvements on many code-related downstream…
Dependency Learning for Legal Judgment Prediction with a Unified Text-to-Text Transformer
Yunyun Huang, Xiaoyu Shen, Chuanyi Li +2
Given the fact of a case, Legal Judgment Prediction (LJP) involves a series of sub-tasks such as predicting violated law articles, charges and term of penalty. We propose leveragin…
AST-Transformer: Encoding Abstract Syntax Trees Efficiently for Code Summarization
Ze Tang, Chuanyi Li, Jidong Ge +3
Code summarization aims to generate brief natural language descriptions for source code. As source code is highly structured and follows strict programming language grammars, its A…
Learning Fine-grained Fact-Article Correspondence in Legal Cases
Jidong Ge, Yunyun huang, Xiaoyu Shen +2
Automatically recommending relevant law articles to a given legal case has attracted much attention as it can greatly release human labor from searching over the large database of…
Delving into Variance Transmission and Normalization: Shift of Average Gradient Makes the Network Collapse
Yuxiang Liu, Jidong Ge, Chuanyi Li +1
Normalization operations are essential for state-of-the-art neural networks and enable us to train a network from scratch with a large learning rate (LR). We attempt to explain the…
Synergy between Machine/Deep Learning and Software Engineering: How Far Are We?
Simin Wang, Liguo Huang, Jidong Ge +5
Since 2009, the deep learning revolution, which was triggered by the introduction of ImageNet, has stimulated the synergy between Machine Learning (ML)/Deep Learning (DL) and Softw…