Search Results for author: Thong Nguyen

Found 36 papers, 21 papers with code

Temporal-Oriented Recipe for Transferring Large Vision-Language Model to Video Understanding

1 code implementation19 May 2025 Thong Nguyen, Zhiyuan Hu, Xu Lin, Cong-Duy Nguyen, See-Kiong Ng, Luu Anh Tuan

In this work, we conduct a thorough empirical study to demystify crucial components that influence the temporal understanding of LVLMs.

Language Modeling Language Modelling +2

Effective Inference-Free Retrieval for Learned Sparse Representations

no code implementations30 Apr 2025 Franco Maria Nardini, Thong Nguyen, Cosimo Rulli, Rossano Venturini, Andrew Yates

In this paper, we conduct an extended evaluation of regularization approaches for LSR where we discuss their effectiveness, efficiency, and out-of-domain generalization capabilities.

Domain Generalization Retrieval

Leveraging Decoder Architectures for Learned Sparse Retrieval

no code implementations25 Apr 2025 Jingfen Qiao, Thong Nguyen, Evangelos Kanoulas, Andrew Yates

Learned Sparse Retrieval (LSR) has traditionally focused on small-scale encoder-only transformer architectures.

Decoder Retrieval

CutPaste&Find: Efficient Multimodal Hallucination Detector with Visual-aid Knowledge Base

no code implementations18 Feb 2025 Cong-Duy Nguyen, Xiaobao Wu, Duc Anh Vu, Shuai Zhao, Thong Nguyen, Anh Tuan Luu

Large Vision-Language Models (LVLMs) have demonstrated impressive multimodal reasoning capabilities, but they remain susceptible to hallucination, particularly object hallucination where non-existent objects or incorrect attributes are fabricated in generated descriptions.

Attribute Hallucination +2

DyVo: Dynamic Vocabularies for Learned Sparse Retrieval with Entities

1 code implementation10 Oct 2024 Thong Nguyen, Shubham Chatterjee, Sean MacAvaney, Iain Mackie, Jeff Dalton, Andrew Yates

Learned Sparse Retrieval (LSR) models use vocabularies from pre-trained transformers, which often split entities into nonsensical fragments.

Document Ranking Entity Embeddings +3

Topic-aware Causal Intervention for Counterfactual Detection

no code implementations25 Sep 2024 Thong Nguyen, Truc-My Nguyen

Hence, we consider the problem of counterfactual detection (CFD) and seek to enhance the CFD models.

counterfactual Counterfactual Detection

MAMA: Meta-optimized Angular Margin Contrastive Framework for Video-Language Representation Learning

1 code implementation4 Jul 2024 Thong Nguyen, Yi Bin, Xiaobao Wu, Xinshuai Dong, Zhiyuan Hu, Khoi Le, Cong-Duy Nguyen, See-Kiong Ng, Luu Anh Tuan

To address these problems, we propose MAMA, a new approach to learning video-language representations by utilizing a contrastive objective with a subtractive angular margin to regularize cross-modal representations in their effort to reach perfect similarity.

Language Modeling Language Modelling +4

Modeling Dynamic Topics in Chain-Free Fashion by Evolution-Tracking Contrastive Learning and Unassociated Word Exclusion

2 code implementations28 May 2024 Xiaobao Wu, Xinshuai Dong, Liangming Pan, Thong Nguyen, Anh Tuan Luu

However, existing models suffer from repetitive topic and unassociated topic issues, failing to reveal the evolution and hindering further applications.

Contrastive Learning Diversity +2

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 Text 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 Diversity +2

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 Text Retrieval

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.

Survey Topic Models

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

2 code implementations25 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.

Decoder Diversity +1

READ: 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 Modeling Language Modelling +1

Expand BERT Representation with Visual Information via Grounded Language Learning with Multimodal Partial Alignment

no code implementations4 Dec 2023 Cong-Duy Nguyen, The-Anh Vu-Le, Thong Nguyen, Tho Quan, Luu Anh Tuan

Language models have been supervised with both language-only objective and visual grounding in existing studies of visual-grounded language learning.

Grounded language learning Language Modeling +4

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

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 Modeling Language Modelling +2

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.

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

2 code implementations7 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

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

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 multimodal interaction

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.

Diversity image-classification +6

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

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

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 model +1

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

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

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

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