87 citations · 170 across the 19 of their papers we have counts for
10 papers · 1 filter
Exploring Representation-Level Augmentation for Code Search
Haochen Li, Chunyan Miao, Cyril Leung +4
Code search, which aims at retrieving the most relevant code fragment for a given natural language query, is a common activity in software development practice. Recently, contrasti…
Unveiling the Black Box of PLMs with Semantic Anchors: Towards Interpretable Neural Semantic Parsing
Lunyiu Nie, Jiuding Sun, Yanlin Wang +6
The recent prevalence of pretrained language models (PLMs) has dramatically shifted the paradigm of semantic parsing, where the mapping from natural language utterances to structur…
Make Heterophily Graphs Better Fit GNN: A Graph Rewiring Approach
Wendong Bi, Lun Du, Qiang Fu +3
Graph Neural Networks (GNNs) are popular machine learning methods for modeling graph data. A lot of GNNs perform well on homophily graphs while having unsatisfactory performance on…
Revisiting Code Search in a Two-Stage Paradigm
Fan Hu, Yanlin Wang, Lun Du +4
With a good code search engine, developers can reuse existing code snippets and accelerate software development process. Current code search methods can be divided into two categor…
Tackling Long Code Search with Splitting, Encoding, and Aggregating
Fan Hu, Yanlin Wang, Lun Du +4
Code search with natural language helps us reuse existing code snippets. Thanks to the Transformer-based pretraining models, the performance of code search has been improved signif…
MM-GNN: Mix-Moment Graph Neural Network towards Modeling Neighborhood Feature Distribution
Wendong Bi, Lun Du, Qiang Fu +3
Graph Neural Networks (GNNs) have shown expressive performance on graph representation learning by aggregating information from neighbors. Recently, some studies have discussed the…
CoCoSoDa: Effective Contrastive Learning for Code Search
Ensheng Shi, Yanlin Wang, Wenchao Gu +5
Code search aims to retrieve semantically relevant code snippets for a given natural language query. Recently, many approaches employing contrastive learning have shown promising r…
Accelerating Code Search with Deep Hashing and Code Classification
Wenchao Gu, Yanlin Wang, Lun Du +4
Code search is to search reusable code snippets from source code corpus based on natural languages queries. Deep learning-based methods of code search have shown promising results.…
UniXcoder: Unified Cross-Modal Pre-training for Code Representation
Daya Guo, Shuai Lu, Nan Duan +3
Pre-trained models for programming languages have recently demonstrated great success on code intelligence. To support both code-related understanding and generation tasks, recent…
RACE: Retrieval-Augmented Commit Message Generation
Ensheng Shi, Yanlin Wang, Wei Tao +5
Commit messages are important for software development and maintenance. Many neural network-based approaches have been proposed and shown promising results on automatic commit mess…