Search Results for author: Xiaobao Wu

Found 16 papers, 14 papers with code

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

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

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

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

Towards the TopMost: A Topic Modeling System Toolkit

1 code implementation13 Sep 2023 Xiaobao Wu, Fengjun Pan, Anh Tuan Luu

Topic models have been proposed for decades with various applications and recently refreshed by the neural variational inference.

Topic Models Variational Inference

Fact-Checking Complex Claims with Program-Guided Reasoning

1 code implementation22 May 2023 Liangming Pan, Xiaobao Wu, Xinyuan Lu, Anh Tuan Luu, William Yang Wang, Min-Yen Kan, Preslav Nakov

Fact-checking real-world claims often requires collecting multiple pieces of evidence and applying complex multi-step reasoning.

Fact Checking In-Context Learning

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.

Zero-Shot Text Classification via Self-Supervised Tuning

1 code implementation19 May 2023 Chaoqun Liu, Wenxuan Zhang, Guizhen Chen, Xiaobao Wu, Anh Tuan Luu, Chip Hong Chang, Lidong Bing

In this work, we propose a new paradigm based on self-supervised learning to solve zero-shot text classification tasks by tuning the language models with unlabeled data, called self-supervised tuning.

Self-Supervised Learning Sentence +5

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

Mitigating Data Sparsity for Short Text Topic Modeling by Topic-Semantic Contrastive Learning

1 code implementation23 Nov 2022 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 word co-occurrence information.

Contrastive Learning Data Augmentation

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

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

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