Journal Papers:

Finding Environmental-friendly Chemical Synthesis with AI and High-throughput Robotics
Vu Van Hao, Bui Khanh Huyen, Dang Dinh Dang Khoa, Duong Tuan Manh, Dung D. Le, Tung Nguyen-Dang
Journal of Science: Advanced Materials and Devices (Q1) (Paper)

Towards Efficient Pareto-optimal Utility-Fairness between Groups in Repeated Rankings
Phuong Dinh Mai, Duc-Trong Le, Tuan-Anh Hoang, Dung D. Le
Machine Learning Journal, ACML 2024 Special Issue (Paper)

A Framework for Controllable Pareto Front Learning with Completed Scalarization Functions and its Applications
Tran Anh Tuan, Long P. Hoang, Dung D. Le, Tran Ngoc Thang
Neural Networks Journal, Jan 2024 (Paper)

Enhancing Few-shot Image Classification with Cosine Transformer
Quang-Huy Nguyen, Cuong Q. Nguyen, Dung D. Le, and Hieu H. Pham
IEEE Access, 2023 (Paper)

Efficient Retrieval of Matrix Factorization-based Top-k Recommendations: A Survey of Recent Approaches
Dung D. Le and Hady W. Lauw
Journal of Artificial Intelligence Research (JAIR), 2021 (Paper)

Conference Papers:

Keyword-driven Retrieval-Augmented Large Language Models for Cold-start User Recommendations
Dang Hai Kieu, Minh Duc Nguyen, Thanh-Son Nguyen, Dung D. Le
The Web Conference 2025, Workshop LLL 4 E-Commerce. (Paper)

VisualCoder: Guiding Large Language Models in Code Execution with Fine-grained Multimodal Chain-of-Thought Reasoning
Cuong Le Chi, Chau Truong Vinh Hoang, Phan Nhật Huy, Dung D. Le, Tien N Nguyen, Nghi D. Q. Bui
The 2025 Annual Conference of the Nations of the Americas Chapter of the ACL (NAACL 2025) (Paper)

Improving Pareto Set Learning for Expensive Multi-Objective Optimization via Stein Variational Hypernetworks
Minh Duc Nguyen, Phuong Mai Dinh, Quang-Huy Nguyen, Hoang Phi Long, Dung D. Le
The 39th Annual AAAI Conference on Artificial Intelligence (AAAI 2025) (Paper)

Experience as Source for Anticipation and Planning: Experiential Policy Learning for Target-driven Recommendation Dialogues
Huy Quang Dao, Yang Deng, Khanh-Huyen Bui, Dung D. Le, Lizi Liao
Findings of EMNLP 2024. (Paper)

A Curious Case of Searching for the Correlation between Training Data and Adversarial Robustness of Transformer Textual Models
Dang Cao Cuong, Dung D. Le, Thai Le
Findings of ACL, 2024. (Paper)

Broadening the View: Demonstration-augmented Prompt Learning for Conversational Recommendation
Huy Dao, Yang Deng, Dung D. Le, Lizi Liao
The 47th ACM SIGIR on Research and Development in Information Retrieval (SIGIR 2024) (Paper)

Improving Vietnamese-English Medical Machine Translation
Nhu Vo, Dat Quoc Nguyen, Dung D. Le, Massimo Piccardi and Wray Buntine
The 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) (Paper)

Towards Efficient Communication and Secure Federated Recommendation System via Low-rank Training
Ngoc-Hieu Nguyen, Tuan-Anh Nguyen, Tuan Minh Nguyen, Vu Tien Hoang, Dung D. Le, Kok-Seng Wong
The 2024 ACM Web Conference (Paper)

Reinforced Target-driven Conversational Promotion
Huy Quang Dao, Lizi Liao, Dung D. Le, Yuxiang Nie
The 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023) (Paper)

Towards Data-Agnostic Pruning At Initialization: What Makes a Good Sparse Mask?
Hoang Pham, The-Anh Ta, Shiwei Liu, Lichuan Xiang, Dung D. Le. Hongkai Wen, Long Tran-Thanh
The 2023 Conference on Neural Processing Systems (NeurIPS 2023) (Paper)

A Probabilistic Framework for Pruning Transformers via a Finite Admixture of Keys
T. Nguyen, T. Nguyen, Long Bui, Hai Do, Dung D. Le, Hung Tran-The, Duy Khuong Nguyen, N. Ho, S. J. Osher, R. G. Baraniuk
The 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2023) (Paper)

Improving Pareto Front Learning via Multi-Sample Hypernetworks
Hoang Phi Long, Dung D. Le, Tran Anh Tuan, Tran Ngoc Thang
AAAI Conference on Artificial Intelligence (AAAI-23) (Paper)

Improving Transformers with Probabilistic Attention Keys
T. Nguyen, T. Nguyen, Dung D. Le, K. Nguyen, A. Tran, R. G. Baraniuk, N. Ho, S. J. Osher
The Thirty-ninth International Conference on Machine Learning (ICML 2022), July 2022 (Paper)

Collaborative Curating for Discovery and Expansion of Visual Clusters
Dung D. Le and Hady W. Lauw
The 15th ACM International Conference in Web Search and Data Mining (WSDM-22), Feb 2022 (Paper)

Stochastically Robust Personalized Ranking for LSH Recommendation Retrieval
Dung D. Le and Hady W. Lauw
AAAI Conference on Artificial Intelligence (AAAI-20), Feb 2020 (Paper)

Learning Multiple Maps from Conditional Ordinal Triplets
Dung D. Le and Hady W. Lauw
International Joint Conference on Artificial Intelligence (IJCAI'19), Aug 2019 (Paper)

Multiperspective Graph-Theoretic Similarity Measure
Dung D. Le and Hady W. Lauw
ACM Conference on Information and Knowledge Management (CIKM'18), Oct 2018 (Paper|Code)

Indexable Bayesian Personalized Ranking for Efficient Top-k Recommendation
Dung D. Le and Hady W. Lauw
ACM Conference on Information and Knowledge Management (CIKM'17), Nov 2017 (Paper|Code)

Euclidean Co-Embedding of Ordinal Data for Multi-Type Visualization
Dung D. Le and Hady W. Lauw
SIAM International Conference on Data Mining (SDM'16), May 2016 (Paper)

Tutorials:

Recent Advances on Scalable Retrieval of Personalized Recommendation
Dung D. Le and Hady W. Lauw
The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19), Jan 2019 (Website| Materials|Videos)

PhD Thesis:

Preference Learning and Similarity Learning Perspectives on Personalized Recommendation
Duy Dung LE, Singapore Management University (Pdf|Blog)