Search Results for author: Anh Tuan Luu

Found 24 papers, 10 papers with code

Vision-and-Language Pretraining

no code implementations5 Jul 2022 Thong Nguyen, Cong-Duy Nguyen, Xiaobao Wu, Anh Tuan Luu

Inheriting the spirit of Transfer Learning, research works in V&L have devised multiple pretraining techniques on large-scale datasets in order to enhance the performance of downstream tasks.

Image Classification Machine Translation +5

Long Range Graph Benchmark

1 code implementation16 Jun 2022 Vijay Prakash Dwivedi, Ladislav Rampášek, Mikhail Galkin, Ali Parviz, Guy Wolf, Anh Tuan Luu, Dominique Beaini

Graph Neural Networks (GNNs) that are based on the message passing (MP) paradigm exchange information between 1-hop neighbors to build node representations at each layer.

Graph Classification Graph Learning +3

Recipe for a General, Powerful, Scalable Graph Transformer

1 code implementation25 May 2022 Ladislav Rampášek, Mikhail Galkin, Vijay Prakash Dwivedi, Anh Tuan Luu, Guy Wolf, Dominique Beaini

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 Classification Graph Property Prediction +3

Certified Robustness Against Natural Language Attacks by Causal Intervention

no code implementations24 May 2022 Haiteng Zhao, Chang Ma*, Xinshuai Dong, Anh Tuan Luu, Zhi-Hong Deng, Hanwang Zhang

Deep learning models have achieved great success in many fields, yet they are vulnerable to adversarial examples.

Contrastive Learning for Neural Topic Model

1 code implementation NeurIPS 2021 Thong Nguyen, Anh Tuan Luu

Recent empirical studies show that adversarial topic models (ATM) can successfully capture semantic patterns of the document by differentiating a document with another dissimilar sample.

Contrastive Learning Topic Models

Grounding Language Representation with Visual Object Information via Cross Modal Pretraining

no code implementations29 Sep 2021 Cong-Duy T Nguyen, Anh Tuan Luu, Tho Quan

However, this approach has two main drawbacks: (i) the whole image usually contains more objects and backgrounds than the sentence itself; thus, matching them together will confuse the grounded model; (ii) CNN only extracts the features of the image but not the relationship between objects inside that, limiting the grounded model to learn complicated contexts.

Grounded language learning

Enriching and Controlling Global Semantics for Text Summarization

no code implementations EMNLP 2021 Thong Nguyen, Anh Tuan Luu, Truc Lu, Tho Quan

Recently, Transformer-based models have been proven effective in the abstractive summarization task by creating fluent and informative summaries.

Abstractive Text Summarization Text Generation

Towards Robustness Against Natural Language Word Substitutions

1 code implementation ICLR 2021 Xinshuai Dong, Anh Tuan Luu, Rongrong Ji, Hong Liu

Robustness against word substitutions has a well-defined and widely acceptable form, i. e., using semantically similar words as substitutions, and thus it is considered as a fundamental stepping-stone towards broader robustness in natural language processing.

Natural Language Inference Natural Language Processing +1

Benchmarking Graph Neural Networks

12 code implementations2 Mar 2020 Vijay Prakash Dwivedi, Chaitanya K. Joshi, Anh Tuan Luu, Thomas Laurent, Yoshua Bengio, Xavier Bresson

In the last few years, graph neural networks (GNNs) have become the standard toolkit for analyzing and learning from data on graphs.

Graph Classification Graph Regression +2

Compositional De-Attention Networks

no code implementations NeurIPS 2019 Yi Tay, Anh Tuan Luu, Aston Zhang, Shuohang Wang, Siu Cheung Hui

Attentional models are distinctly characterized by their ability to learn relative importance, i. e., assigning a different weight to input values.

Machine Translation Natural Language Inference +3

Holographic Factorization Machines for Recommendation

1 code implementation AAAI 2019 Yi Tay, Shuai Zhang, Anh Tuan Luu, Siu Cheung Hui, Lina Yao, Tran Dang Quang Vinh

Factorization Machines (FMs) are a class of popular algorithms that have been widely adopted for collaborative filtering and recommendation tasks.

Collaborative Filtering

Holistic Multi-modal Memory Network for Movie Question Answering

no code implementations12 Nov 2018 Anran Wang, Anh Tuan Luu, Chuan-Sheng Foo, Hongyuan Zhu, Yi Tay, Vijay Chandrasekhar

In this paper, we present the Holistic Multi-modal Memory Network (HMMN) framework which fully considers the interactions between different input sources (multi-modal context, question) in each hop.

Question Answering Video Question Answering

CoupleNet: Paying Attention to Couples with Coupled Attention for Relationship Recommendation

no code implementations29 May 2018 Yi Tay, Anh Tuan Luu, Siu Cheung Hui

Our approach, the CoupleNet is an end-to-end deep learning based estimator that analyzes the social profiles of two users and subsequently performs a similarity match between the users.

Recommendation Systems

Learning to Attend via Word-Aspect Associative Fusion for Aspect-based Sentiment Analysis

1 code implementation14 Dec 2017 Yi Tay, Anh Tuan Luu, Siu Cheung Hui

Our novel model, \textit{Aspect Fusion LSTM} (AF-LSTM) learns to attend based on associative relationships between sentence words and aspect which allows our model to adaptively focus on the correct words given an aspect term.

Aspect-Based Sentiment Analysis

Latent Relational Metric Learning via Memory-based Attention for Collaborative Ranking

1 code implementation17 Jul 2017 Yi Tay, Anh Tuan Luu, Siu Cheung Hui

Our model, LRML (\textit{Latent Relational Metric Learning}) is a novel metric learning approach for recommendation.

 Ranked #1 on Recommendation Systems on Netflix (nDCG@10 metric)

Collaborative Ranking Metric Learning +1

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