Xiaobao Wu
Hi, I'm now a Ph.D. candidate at SCSE, Nanyang Technological University, supervised by Prof.
Anh Tuan Luu.
My research interests lie mostly in the area of machine learning and natural language processing.
Emails: xiaobao002@e.ntu.edu.sg
[Publications]
[Google Scholar]
[Github]
Latest News
- Check out our latest topic model toolkit: TopMost
- May 2024: One paper accepted to ACL 2024 Findings!
- Mar 2024: One paper accepted to NAACL 2024!
- Jan 2024: Our Neural Topic Modeling Survey Paper got accepted to Artificial Intelligence Review!
- Dec 2023: Two papers accepted to AAAI 2024!
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A Survey on Neural Topic Models: Methods, Applications, and Challenges
Xiaobao Wu, Thong Nguyen, Anh Tuan Luu.
Artificial Intelligence Review 2024
[pdf]
[paper list]
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On the Affinity, Rationality, and Diversity of Hierarchical Topic Modeling
Xiaobao Wu, Fengjun Pan, Thong Nguyen, Yichao Feng, Chaoqun Liu, Cong-Duy Nguyen, Anh Tuan Luu.
The AAAI Conference on Artificial Intelligence (AAAI) 2024
[pdf]
[code]
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Topic Modeling as Multi-Objective Contrastive Optimization
Thong Nguyen, Xiaobao Wu, Xinshuai Dong, Cong-Duy Nguyen, See-Kiong Ng, Anh Tuan Luu.
International Conference on Learning Representations (ICLR) 2024
[pdf]
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Effective Neural Topic Modeling with Embedding Clustering Regularization
Xiaobao Wu, Xinshuai Dong, Thong Nguyen, Anh Tuan Luu.
International Conference on Machine Learning (ICML) 2023
[pdf]
[code]
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InfoCTM: A Mutual Information Maximization Perspective of Cross-lingual Topic Modeling
Xiaobao Wu, Xinshuai Dong, Thong Nguyen, Chaoqun Liu, Liangming Pan, Anh Tuan Luu.
The AAAI Conference on Artificial Intelligence (AAAI) 2023
[pdf]
[code]
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Fact-Checking Complex Claims with Program-Guided Reasoning
Liangming Pan, Xiaobao Wu, Xinyuan Lu, Anh Tuan Luu, William Yang Wang, Min-Yen Kan, Preslav Nakov.
The Annual Meeting of the Association for Computational Linguistics (ACL) 2023
[pdf]
[code]
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Mitigating Data Sparsity for Short Text Topic Modeling by Topic-Semantic Contrastive Learning
Xiaobao Wu, Anh Tuan Luu, Xinshuai Dong.
Empirical Methods in Natural Language Processing (EMNLP) 2022
[pdf]
[code]
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Discovering Topics in Long-tailed Corpora with Causal Intervention
Xiaobao Wu, Chunping Li, Yishu Miao.
Findings of the Association for Computational Linguistics (ACL Findings) 2021
[pdf]
[code]
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Short Text Topic Modeling with Topic Distribution Quantization and Negative Sampling Decoder
Xiaobao Wu, Chunping Li, Yan Zhu, Yishu Miao.
Empirical Methods in Natural Language Processing (EMNLP) 2020
[pdf]
[code]
[video]
Short version in NeurIPS Workshop on Information Theory and Machine Learning (ITML) 2019
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Learning Multilingual Topics with Neural Variational Inference
Xiaobao Wu, Chunping Li, Yan Zhu, Yishu Miao.
International Conference on Natural Language Processing and Chinese Computing (NLPCC) 2020 (oral)
[pdf]
[code]
Education
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Nanyang Technological University, Singapore, 2021-2025
Ph.D., SCSE. Advisor: Prof. Anh Tuan Luu
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Tsinghua University, Beijing, China, 2018-2021
M.Eng, School of Software.
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Southeast University, Nanjing, China, 2014-2018
B.E., College of Software Engineering.
Professional Services
PC Member / Reviewer
- ACL (ARR) 2022, 2023, 2024
- EMNLP 2021, 2022, 2023
- ICLR 2023
- AAAI 2024
- TKDE, Computational Linguistics, Information Processing and Management
Honors & Awards
- NTU Research Scholarship (2021-2025)
- Excellent Master Graduate, School of Software, Tsinghua University (2021)
- Tsinghua-Glodon Scholarship, Tsinghua University (2019, 2020)
- Merit Student of Jiangsu Province, Department of Education of Jiangsu Province (2017)
- Merit Student of Southeast University (2015, 2016, 2017)
- First prize in the National Cloud Computing Competition (2017)
- First prize in Chinese Collegiate Computing Competition (2017)
- National Scholarship, Ministry of Education of China (2015, 2016)
Teaching
- TA for Deep Learning For Natural Language Processing, NTU, Spring 2023.
- TA for Artificial Intelligence, NTU, Spring 2023.
- TA for Software Engineering, NTU, Fall 2022.
- TA for Introduction to Artificial Intelligence, Tsinghua University, Spring 2020.
Notes
Here are some personal notes about machine learning from books like PRML or other online resources. If you find
any mistake, please contact me.