87 citations · 390 across the 41 of their papers we have counts for
12 papers · 1 filter
DIGMN: Dynamic Intent Guided Meta Network for Differentiated User Engagement Forecasting in Online Professional Social Platforms
Feifan Li, Lun Du, Qiang Fu +4
User engagement prediction plays a critical role for designing interaction strategies to grow user engagement and increase revenue in online social platforms. Through the in-depth…
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…
Learning Rate Perturbation: A Generic Plugin of Learning Rate Schedule towards Flatter Local Minima
Hengyu Liu, Qiang Fu, Lun Du +4
Learning rate is one of the most important hyper-parameters that has a significant influence on neural network training. Learning rate schedules are widely used in real practice to…
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.…
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…
HTGN-BTW: Heterogeneous Temporal Graph Network with Bi-Time-Window Training Strategy for Temporal Link Prediction
Chongjian Yue, Lun Du, Qiang Fu +4
With the development of temporal networks such as E-commerce networks and social networks, the issue of temporal link prediction has attracted increasing attention in recent years.…
Inferring Network Structure with Unobservable Nodes from Time Series Data
Mengyuan Chen, Yan Zhang, Zhang Zhang +2
Network structures play important roles in social, technological and biological systems. However, the observable nodes and connections in real cases are often incomplete or unavail…