1 citations · 2 across the 7 of their papers we have counts for
6 papers · 1 filter
From Top-1 to Top-K: A Reproducibility Study and Benchmarking of Counterfactual Explanations for Recommender Systems
Quang-Huy Nguyen, Thanh-Hai Nguyen, Khac-Manh Thai +6
Counterfactual explanations (CEs) provide an intuitive way to understand recommender systems by identifying minimal modifications to user-item interactions that alter recommendatio…
Multi-modal Adaptive Mixture of Experts for Cold-start Recommendation
Van-Khang Nguyen, Duc-Hoang Pham, Huy-Son Nguyen +3
Recommendation systems have faced significant challenges in cold-start scenarios, where new items with a limited history of interaction need to be effectively recommended to users.…
RaMen: Multi-Strategy Multi-Modal Learning for Bundle Construction
Huy-Son Nguyen, Quang-Huy Nguyen, Duc-Hoang Pham +5
Existing studies on bundle construction have relied merely on user feedback via bipartite graphs or enhanced item representations using semantic information. These approaches fail…
Personalized Diffusion Model Reshapes Cold-Start Bundle Recommendation
Tuan-Nghia Bui, Huy-Son Nguyen, Cam-Van Thi Nguyen +2
Bundle recommendation aims to recommend a set of items to each user. However, the sparser interactions between users and bundles raise a big challenge, especially in cold-start sce…
BRIDGE: Bundle Recommendation via Instruction-Driven Generation
Tuan-Nghia Bui, Huy-Son Nguyen, Cam-Van Nguyen Thi +2
Bundle recommendation aims to suggest a set of interconnected items to users. However, diverse interaction types and sparse interaction matrices often pose challenges for previous…
Bundle Recommendation with Item-level Causation-enhanced Multi-view Learning
Huy-Son Nguyen, Tuan-Nghia Bui, Long-Hai Nguyen +4
Bundle recommendation aims to enhance business profitability and user convenience by suggesting a set of interconnected items. In real-world scenarios, leveraging the impact of asy…