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08/25/2023
SoTaNa: The Open-Source Software Development Assistant
Software development plays a crucial role in driving innovation and effi...
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06/06/2023
On Manipulating Signals of User-Item Graph: A Jacobi Polynomial-based Graph Collaborative Filtering
Collaborative filtering (CF) is an important research direction in recom...
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05/24/2023
GPT4Graph: Can Large Language Models Understand Graph Structured Data ? An Empirical Evaluation and Benchmarking
Large language models (LLM) like ChatGPT have become indispensable to ar...
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05/24/2023
Leveraging LLMs for KPIs Retrieval from Hybrid Long-Document: A Comprehensive Framework and Dataset
Large Language Models (LLMs) demonstrate exceptional performance in text...
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05/22/2023
Causal-Based Supervision of Attention in Graph Neural Network: A Better and Simpler Choice towards Powerful Attention
In recent years, attention mechanisms have demonstrated significant pote...
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04/11/2023
Towards Efficient Fine-tuning of Pre-trained Code Models: An Experimental Study and Beyond
Recently, fine-tuning pre-trained code models such as CodeBERT on downst...
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02/16/2023
Robust Mid-Pass Filtering Graph Convolutional Networks
Graph convolutional networks (GCNs) are currently the most promising par...
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02/13/2023
Homophily-oriented Heterogeneous Graph Rewiring
With the rapid development of the World Wide Web (WWW), heterogeneous gr...
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10/22/2022
DIGMN: Dynamic Intent Guided Meta Network for Differentiated User Engagement Forecasting in Online Professional Social Platforms
User engagement prediction plays a critical role for designing interacti...
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10/04/2022
Guiding the PLMs with Semantic Anchors as Intermediate Supervision: Towards Interpretable Semantic Parsing
The recent prevalence of pretrained language models (PLMs) has dramatica...
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09/17/2022
Make Heterophily Graphs Better Fit GNN: A Graph Rewiring Approach
Graph Neural Networks (GNNs) are popular machine learning methods for mo...
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08/25/2022
Learning Rate Perturbation: A Generic Plugin of Learning Rate Schedule towards Flatter Local Minima
Learning rate is one of the most important hyper-parameters that has a s...
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08/15/2022
MM-GNN: Mix-Moment Graph Neural Network towards Modeling Neighborhood Feature Distribution
Graph Neural Networks (GNNs) have shown expressive performance on graph ...
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04/07/2022
Enhancing Semantic Code Search with Multimodal Contrastive Learning and Soft Data Augmentation
Code search aims to retrieve the most semantically relevant code snippet...
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03/29/2022
Accelerating Code Search with Deep Hashing and Code Classification
Code search is to search reusable code snippets from source code corpus ...
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03/05/2022
ECMG: Exemplar-based Commit Message Generation
Commit messages concisely describe the content of code diffs (i.e., code...
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02/25/2022
HTGN-BTW: Heterogeneous Temporal Graph Network with Bi-Time-Window Training Strategy for Temporal Link Prediction
With the development of temporal networks such as E-commerce networks an...
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12/02/2021
Source Free Unsupervised Graph Domain Adaptation
Graph Neural Networks (GNNs) have achieved great success on a variety of...
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11/30/2021
Neuron with Steady Response Leads to Better Generalization
Regularization can mitigate the generalization gap between training and ...
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10/29/2021
GBK-GNN: Gated Bi-Kernel Graph Neural Networks for Modeling Both Homophily and Heterophily
Graph Neural Networks (GNNs) are widely used on a variety of graph-based...
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08/30/2021
CAST: Enhancing Code Summarization with Hierarchical Splitting and Reconstruction of Abstract Syntax Trees
Code summarization aims to generate concise natural language description...
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08/14/2021
Neuron Campaign for Initialization Guided by Information Bottleneck Theory
Initialization plays a critical role in the training of deep neural netw...
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07/15/2021
Neural Code Summarization: How Far Are We?
Source code summaries are important for the comprehension and maintenanc...
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07/12/2021
On the Evaluation of Commit Message Generation Models: An Experimental Study
Commit messages are natural language descriptions of code changes, which...
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07/10/2021
Is a Single Model Enough? MuCoS: A Multi-Model Ensemble Learning for Semantic Code Search
Recently, deep learning methods have become mainstream in code search si...
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07/05/2021
CoCoSum: Contextual Code Summarization with Multi-Relational Graph Neural Network
Source code summaries are short natural language descriptions of code sn...
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06/06/2021
TabularNet: A Neural Network Architecture for Understanding Semantic Structures of Tabular Data
Tabular data are ubiquitous for the widespread applications of tables an...
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05/17/2021
Understanding and Improvement of Adversarial Training for Network Embedding from an Optimization Perspective
Network Embedding aims to learn a function mapping the nodes to Euclidea...
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11/30/2020
TSSRGCN: Temporal Spectral Spatial Retrieval Graph Convolutional Network for Traffic Flow Forecasting
Traffic flow forecasting is of great significance for improving the effi...
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01/18/2020
Inference for Network Structure and Dynamics from Time Series Data via Graph Neural Network
Network structures in various backgrounds play important roles in social...
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06/03/2019
