244 citations · 1.3k across the 96 of their papers we have counts for
8 papers · 1 filter
Mitigating Data Sparsity for Short Text Topic Modeling by Topic-Semantic Contrastive Learning
Xiaobao Wu, Anh Tuan Luu, Xinshuai Dong
To overcome the data sparsity issue in short text topic modeling, existing methods commonly rely on data augmentation or the data characteristic of short texts to introduce more wo…
How to train your draGAN: A task oriented solution to imbalanced classification
Leon O. Guertler, Andri Ashfahani, Anh Tuan Luu
The long-standing challenge of building effective classification models for small and imbalanced datasets has seen little improvement since the creation of the Synthetic Minority O…
Exploiting Contrastive Learning and Numerical Evidence for Confusing Legal Judgment Prediction
Leilei Gan, Baokui Li, Kun Kuang +5
Given the fact description text of a legal case, legal judgment prediction (LJP) aims to predict the case's charge, law article and penalty term. A core problem of LJP is how to di…
Adaptive Contrastive Learning on Multimodal Transformer for Review Helpfulness Predictions
Thong Nguyen, Xiaobao Wu, Anh-Tuan Luu +3
Modern Review Helpfulness Prediction systems are dependent upon multiple modalities, typically texts and images. Unfortunately, those contemporary approaches pay scarce attention t…
Vision-and-Language Pretraining
Thong Nguyen, Cong-Duy Nguyen, Xiaobao Wu +2
With the burgeoning amount of data of image-text pairs and diversity of Vision-and-Language (V\&L) tasks, scholars have introduced an abundance of deep learning models in this rese…
Long Range Graph Benchmark
Vijay Prakash Dwivedi, Ladislav Rampášek, Mikhail Galkin +4
Graph Neural Networks (GNNs) that are based on the message passing (MP) paradigm generally exchange information between 1-hop neighbors to build node representations at each layer.…
Recipe for a General, Powerful, Scalable Graph Transformer
Ladislav Rampášek, Mikhail Galkin, Vijay Prakash Dwivedi +3
We propose a recipe on how to build a general, powerful, scalable (GPS) graph Transformer with linear complexity and state-of-the-art results on a diverse set of benchmarks. Graph…
Certified Robustness Against Natural Language Attacks by Causal Intervention
Haiteng Zhao, Chang Ma, Xinshuai Dong +3
Deep learning models have achieved great success in many fields, yet they are vulnerable to adversarial examples. This paper follows a causal perspective to look into the adversari…