3 papers
eess.SP2026
Transformer-Enhanced Reinforcement Learning: Fundamentals and Applications in Communication Networks
Nguyen Cong Luong, Shaohan Feng, Nguyen Duc Hai +10
Reinforcement Learning (RL) has long been a powerful solution to various problems in communication networks. However, traditional RL models still face with several limitations. Not…
cs.LG2025
One-Prompt Strikes Back: Sparse Mixture of Experts for Prompt-based Continual Learning
Minh Le, Bao-Ngoc Dao, Huy Nguyen +3
Prompt-based methods have recently gained prominence in Continual Learning (CL) due to their strong performance and memory efficiency. A prevalent strategy in this paradigm assigns…
cs.LG2025
Revisit Visual Prompt Tuning: The Expressiveness of Prompt Experts
Minh Le, Anh Nguyen, Huy Nguyen +3
Visual Prompt Tuning (VPT) has proven effective for parameter-efficient adaptation of pre-trained vision models to downstream tasks by inserting task-specific learnable prompt toke…