PUBLICATIONS

• 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

The 2024 Conference on Empirical Methods in Natural Language Processing (Findings of EMNLP2024)

• 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 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, Code).

• 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 (Paper, Dataset)

• 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 ACM Web Conference, 2024 (Paper, Code)

• 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, 2024 (Paper, Code)

• 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 Information Processing Systems, NeurIPS 2023 (Paper) 

• Enhancing Few-shot Image Classification with Cosine Transformer

Quang-Huy Nguyen, Cuong Q. Nguyen, Dung D. Le, and Hieu H. Pham

IEEE Access Journal, 2023 (Paper)

• Probabilistic Framework for Pruning Transformers via a Finite Admixture of Keys 

Tan M. Nguyen, Tam Nguyen, Long Bui, Hai Do, Dung D. Le, Hung Tran-The, Khuong Nguyen, Richard G. Baraniuk, Nhat Ho, Stanley J. Osher. 

The 2023 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

The 37th AAAI Conference on Artificial Intelligence (AAAI-23), 2023 (Paper)

• Pruning Deep Equilibrium Models

Hoang Pham, Tuc Nguyen, The-Anh Ta, Dung D. Le, Long Tran-Thanh

ICML 2022 Workshop on Sparsity in Neural Networks (SNN 2022), 2022 (Paper)

• Towards Efficient and Explainable Distracted Driver Detection

Thanh Tran and Dung D. Le

IJCAI 2022 Workshop on Workshop on Artificial Intelligence for Autonomous Driving (AI4AD), 2022 (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)

• Learning Weighted Product Spaces Representations for Graphs of Heterogeneous Structures

Tuc Van Nguyen and Dung D. Le and Anh Ta

ICLR 2022 Workshop on Geometrical and Topological Representation Learning, 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)