b'Shi Han'

research

∙ 08/25/2023

SoTaNa: The Open-Source Software Development Assistant

Software development plays a crucial role in driving innovation and effi...

0 Ensheng Shi, et al. ∙

research

∙ 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...

0 Jiayan Guo, et al. ∙

research

∙ 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...

0 Chongjian Yue, et al. ∙

research

∙ 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...

0 Hongjun Wang, et al. ∙

research

∙ 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...

0 Ensheng Shi, et al. ∙

research

∙ 04/02/2023

Demonstration of InsightPilot: An LLM-Empowered Automated Data Exploration System

Exploring data is crucial in data analysis, as it helps users understand...

0 Pingchuan Ma, et al. ∙

research

∙ 02/16/2023

Robust Mid-Pass Filtering Graph Convolutional Networks

Graph convolutional networks (GCNs) are currently the most promising par...

1 Jincheng Huang, et al. ∙

research

∙ 02/13/2023

Homophily-oriented Heterogeneous Graph Rewiring

With the rapid development of the World Wide Web (WWW), heterogeneous gr...

0 Jiayan Guo, et al. ∙

research

∙ 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...

0 Feifan Li, et al. ∙

research

∙ 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...

0 Lunyiu Nie, et al. ∙

research

∙ 09/17/2022

Make Heterophily Graphs Better Fit GNN: A Graph Rewiring Approach

Graph Neural Networks (GNNs) are popular machine learning methods for mo...

1 Wendong Bi, et al. ∙

research

∙ 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...

0 Hengyu Liu, et al. ∙

research

∙ 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 ...

1 Wendong Bi, et al. ∙

research

∙ 07/26/2022

XInsight: eXplainable Data Analysis Through The Lens of Causality

In light of the growing popularity of Exploratory Data Analysis (EDA), u...

12 Pingchuan Ma, et al. ∙

research

∙ 05/25/2022

PLOG: Table-to-Logic Pretraining for Logical Table-to-Text Generation

Logical table-to-text generation is a task that involves generating logi...

0 Ao Liu, et al. ∙

research

∙ 04/21/2022

LibDB: An Effective and Efficient Framework for Detecting Third-Party Libraries in Binaries

Third-party libraries (TPLs) are reused frequently in software applicati...

0 Wei Tang, et al. ∙

research

∙ 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...

0 Ensheng Shi, et al. ∙

research

∙ 03/29/2022

Accelerating Code Search with Deep Hashing and Code Classification

Code search is to search reusable code snippets from source code corpus ...

0 Wenchao Gu, et al. ∙

research

∙ 03/05/2022

ECMG: Exemplar-based Commit Message Generation

Commit messages concisely describe the content of code diffs (i.e., code...

0 Ensheng Shia, et al. ∙

research

∙ 12/02/2021

Source Free Unsupervised Graph Domain Adaptation

Graph Neural Networks (GNNs) have achieved great success on a variety of...

0 Haitao Mao, et al. ∙

research

∙ 11/30/2021

Neuron with Steady Response Leads to Better Generalization

Regularization can mitigate the generalization gap between training and ...

0 Qiang Fu, et al. ∙

research

∙ 11/16/2021

A Unified and Fast Interpretable Model for Predictive Analytics

In this paper, we propose FXAM (Fast and eXplainable Additive Model), a ...

0 Rui Ding, et al. ∙

research

∙ 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...

0 Lun Du, et al. ∙

research

∙ 10/01/2021

ML4C: Seeing Causality Through Latent Vicinity

Supervised Causal Learning (SCL) aims to learn causal relations from obs...

0 Haoyue Dai, et al. ∙

research

∙ 09/15/2021

FORTAP: Using Formulae for Numerical-Reasoning-Aware Table Pretraining

Tables store rich numerical data, but numerical reasoning over tables is...

0 Zhoujun Cheng, et al. ∙

research

∙ 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...

0 Ensheng Shi, et al. ∙

research

∙ 08/15/2021

HiTab: A Hierarchical Table Dataset for Question Answering and Natural Language Generation

Tables are often created with hierarchies, but existing works on table r...

0 Zhoujun Cheng, et al. ∙

research

∙ 08/14/2021

Neuron Campaign for Initialization Guided by Information Bottleneck Theory

Initialization plays a critical role in the training of deep neural netw...

0 Haitao Mao, et al. ∙

research

∙ 07/15/2021

Neural Code Summarization: How Far Are We?

Source code summaries are important for the comprehension and maintenanc...

14 Ensheng Shi, et al. ∙

research

∙ 07/12/2021

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

Commit messages are natural language descriptions of code changes, which...

0 Wei Tao, et al. ∙

research

∙ 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...

0 Lun Du, et al. ∙

research

∙ 07/05/2021

CoCoSum: Contextual Code Summarization with Multi-Relational Graph Neural Network

Source code summaries are short natural language descriptions of code sn...

0 Yanlin Wang, et al. ∙

research

∙ 06/25/2021

TableSense: Spreadsheet Table Detection with Convolutional Neural Networks

Spreadsheet table detection is the task of detecting all tables on a giv...

0 Haoyu Dong, et al. ∙

research

∙ 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...

0 Lun Du, et al. ∙

research

∙ 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...

0 Lun Du, et al. ∙

research

∙ 10/21/2020

Structure-aware Pre-training for Table Understanding with Tree-based Transformers

Tables are widely used with various structures to organize and present d...

0 Zhiruo Wang, et al. ∙

research

∙ 08/24/2020

Table2Charts: Learning Shared Representations for Recommending Charts on Multi-dimensional Data

It is common for people to create different types of charts to explore a...

0 Mengyu Zhou, et al. ∙

research

∙ 12/28/2017

Automated Refactoring of Nested-IF Formulae in Spreadsheets

Spreadsheets are the most popular end-user programming software, where f...

0 Jie Zhang, et al. ∙

Shi Han

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