Search Results for author: Thong Nguyen

Found 24 papers, 15 papers with code

A Survey on Neural Topic Models: Methods, Applications, and Challenges

2 code implementations27 Jan 2024 Xiaobao Wu, Thong Nguyen, Anh Tuan Luu

In this paper, we present a comprehensive survey on neural topic models concerning methods, applications, and challenges.

Topic Models

A Unified Framework for Learned Sparse Retrieval

1 code implementation23 Mar 2023 Thong Nguyen, Sean MacAvaney, Andrew Yates

We then reproduce all prominent methods using a common codebase and re-train them in the same environment, which allows us to quantify how components of the framework affect effectiveness and efficiency.

Retrieval

Contrastive Learning for Neural Topic Model

2 code implementations 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

InfoCTM: A Mutual Information Maximization Perspective of Cross-Lingual Topic Modeling

1 code implementation7 Apr 2023 Xiaobao Wu, Xinshuai Dong, Thong Nguyen, Chaoqun Liu, Liangming Pan, Anh Tuan Luu

Instead of the direct alignment in previous work, we propose a topic alignment with mutual information method.

Topic Models

Improving Neural Cross-Lingual Summarization via Employing Optimal Transport Distance for Knowledge Distillation

1 code implementation7 Dec 2021 Thong Nguyen, Luu Anh Tuan

Current state-of-the-art cross-lingual summarization models employ multi-task learning paradigm, which works on a shared vocabulary module and relies on the self-attention mechanism to attend among tokens in two languages.

Knowledge Distillation Multi-Task Learning

Improving the Generalizability of Depression Detection by Leveraging Clinical Questionnaires

1 code implementation ACL 2022 Thong Nguyen, Andrew Yates, Ayah Zirikly, Bart Desmet, Arman Cohan

In dataset-transfer experiments on three social media datasets, we find that grounding the model in PHQ9's symptoms substantially improves its ability to generalize to out-of-distribution data compared to a standard BERT-based approach.

Depression Detection Domain Generalization

READ-PVLA: Recurrent Adapter with Partial Video-Language Alignment for Parameter-Efficient Transfer Learning in Low-Resource Video-Language Modeling

1 code implementation12 Dec 2023 Thong Nguyen, Xiaobao Wu, Xinshuai Dong, Khoi Le, Zhiyuan Hu, Cong-Duy Nguyen, See-Kiong Ng, Luu Anh Tuan

Fully fine-tuning pretrained large-scale transformer models has become a popular paradigm for video-language modeling tasks, such as temporal language grounding and video-language summarization.

Language Modelling Transfer Learning

Vision-and-Language Pretraining

1 code implementation5 Jul 2022 Thong Nguyen, Cong-Duy Nguyen, Xiaobao Wu, See-Kiong Ng, Anh Tuan Luu

Moreover, a list of training datasets and downstream tasks is supplied to further polish the perspective into V\&L pretraining.

Image Classification Machine Translation +4

Gradient-Boosted Decision Tree for Listwise Context Model in Multimodal Review Helpfulness Prediction

1 code implementation22 May 2023 Thong Nguyen, Xiaobao Wu, Xinshuai Dong, Anh Tuan Luu, Cong-Duy Nguyen, Zhen Hai, Lidong Bing

Multimodal Review Helpfulness Prediction (MRHP) aims to rank product reviews based on predicted helpfulness scores and has been widely applied in e-commerce via presenting customers with useful reviews.

Adaptive Contrastive Learning on Multimodal Transformer for Review Helpfulness Predictions

1 code implementation7 Nov 2022 Thong Nguyen, Xiaobao Wu, Anh-Tuan Luu, Cong-Duy Nguyen, Zhen Hai, Lidong Bing

To overcome the aforementioned issues, we propose Multimodal Contrastive Learning for Multimodal Review Helpfulness Prediction (MRHP) problem, concentrating on mutual information between input modalities to explicitly elaborate cross-modal relations.

Contrastive Learning

On the Affinity, Rationality, and Diversity of Hierarchical Topic Modeling

1 code implementation25 Jan 2024 Xiaobao Wu, Fengjun Pan, Thong Nguyen, Yichao Feng, Chaoqun Liu, Cong-Duy Nguyen, Anh Tuan Luu

Hierarchical topic modeling aims to discover latent topics from a corpus and organize them into a hierarchy to understand documents with desirable semantic granularity.

document understanding

Multimodal Learned Sparse Retrieval with Probabilistic Expansion Control

1 code implementation27 Feb 2024 Thong Nguyen, Mariya Hendriksen, Andrew Yates, Maarten de Rijke

Our proposed approach efficiently transforms dense vectors from a frozen dense model into sparse lexical vectors.

Image Retrieval Retrieval +1

Adapting Learned Sparse Retrieval for Long Documents

1 code implementation29 May 2023 Thong Nguyen, Sean MacAvaney, Andrew Yates

We investigate existing aggregation approaches for adapting LSR to longer documents and find that proximal scoring is crucial for LSR to handle long documents.

Language Modelling Masked Language Modeling +1

Fast Transient Simulation of High-Speed Channels Using Recurrent Neural Network

no code implementations25 Jan 2019 Thong Nguyen, Tianjian Lu, Ken Wu, Jose Schutt-Aine

In this paper, we leverage machine learning methods, to be specific, the recurrent neural network (RNN), to generate black-box macromodels and achieve significant reduction of computation time.

Vocal Bursts Intensity Prediction

Adaptive Name Entity Recognition under Highly Unbalanced Data

no code implementations10 Mar 2020 Thong Nguyen, Duy Nguyen, Pramod Rao

For several purposes in Natural Language Processing (NLP), such as Information Extraction, Sentiment Analysis or Chatbot, Named Entity Recognition (NER) holds an important role as it helps to determine and categorize entities in text into predefined groups such as the names of persons, locations, quantities, organizations or percentages, etc.

Chatbot named-entity-recognition +4

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

Generative Retrieval as Dense Retrieval

no code implementations20 Jun 2023 Thong Nguyen, Andrew Yates

Generative retrieval is a promising new neural retrieval paradigm that aims to optimize the retrieval pipeline by performing both indexing and retrieval with a single transformer model.

Retrieval

Topic Modeling as Multi-Objective Contrastive Optimization

no code implementations12 Feb 2024 Thong Nguyen, Xiaobao Wu, Xinshuai Dong, Cong-Duy T Nguyen, See-Kiong Ng, Anh Tuan Luu

Secondly, we explicitly cast contrastive topic modeling as a gradient-based multi-objective optimization problem, with the goal of achieving a Pareto stationary solution that balances the trade-off between the ELBO and the contrastive objective.

Contrastive Learning Representation Learning +1

Multimodal Learned Sparse Retrieval for Image Suggestion

no code implementations12 Feb 2024 Thong Nguyen, Mariya Hendriksen, Andrew Yates

Motivated by this, in this work, we explore the application of LSR in the multi-modal domain, i. e., we focus on Multi-Modal Learned Sparse Retrieval (MLSR).

Image Captioning Retrieval +1

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