4 papers
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…
Counterfactual Understanding via Retrieval-aware Multimodal Modeling for Time-to-Event Survival Prediction
Ha-Anh Hoang Nguyen, Tri-Duc Phan Le, Duc-Hoang Pham +4
This paper tackles the problem of time-to-event counterfactual survival prediction, aiming to optimize individualized survival outcomes in the presence of heterogeneity and censore…
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…