99 citations · 588 across the 52 of their papers we have counts for
20 papers · 1 filter
LUNA: Language Understanding with Number Augmentations on Transformers via Number Plugins and Pre-training
Hongwei Han, Jialiang Xu, Mengyu Zhou +3
Transformers are widely used in NLP tasks. However, current approaches to leveraging transformers to understand language expose one weak spot: Number understanding. In some scenari…
Towards Robust Numerical Question Answering: Diagnosing Numerical Capabilities of NLP Systems
Jialiang Xu, Mengyu Zhou, Xinyi He +2
Numerical Question Answering is the task of answering questions that require numerical capabilities. Previous works introduce general adversarial attacks to Numerical Question Answ…
FormLM: Recommending Creation Ideas for Online Forms by Modelling Semantic and Structural Information
Yijia Shao, Mengyu Zhou, Yifan Zhong +5
Online forms are widely used to collect data from human and have a multi-billion market. Many software products provide online services for creating semi-structured forms where que…
Reflection of Thought: Inversely Eliciting Numerical Reasoning in Language Models via Solving Linear Systems
Fan Zhou, Haoyu Dong, Qian Liu +3
Numerical reasoning over natural language has been a long-standing goal for the research community. However, cutting-edge language models have proven difficult to reliably generali…
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…
ASTA: Learning Analytical Semantics over Tables for Intelligent Data Analysis and Visualization
Lingbo Li, Tianle Li, Xinyi He +3
Intelligent analysis and visualization of tables use techniques to automatically recommend useful knowledge from data, thus freeing users from tedious multi-dimension data mining.…
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…
XInsight: eXplainable Data Analysis Through The Lens of Causality
Pingchuan Ma, Rui Ding, Shuai Wang +2
In light of the growing popularity of Exploratory Data Analysis (EDA), understanding the underlying causes of the knowledge acquired by EDA is crucial. However, it remains under-re…
TaCube: Pre-computing Data Cubes for Answering Numerical-Reasoning Questions over Tabular Data
Fan Zhou, Mengkang Hu, Haoyu Dong +3
Existing auto-regressive pre-trained language models (PLMs) like T5 and BART, have been well applied to table question answering by UNIFIEDSKG and TAPEX, respectively, and demonstr…
PLOG: Table-to-Logic Pretraining for Logical Table-to-Text Generation
Ao Liu, Haoyu Dong, Naoaki Okazaki +2
Logical table-to-text generation is a task that involves generating logically faithful sentences from tables, which requires models to derive logical level facts from table records…
LibDB: An Effective and Efficient Framework for Detecting Third-Party Libraries in Binaries
Wei Tang, Yanlin Wang, Hongyu Zhang +3
Third-party libraries (TPLs) are reused frequently in software applications for reducing development cost. However, they could introduce security risks as well. Many TPL detection…
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…
Table Pre-training: A Survey on Model Architectures, Pre-training Objectives, and Downstream Tasks
Haoyu Dong, Zhoujun Cheng, Xinyi He +6
Since a vast number of tables can be easily collected from web pages, spreadsheets, PDFs, and various other document types, a flurry of table pre-training frameworks have been prop…