activity
20242026
most citedBundle Recommendation with Item-level Causation-enhanced Multi-view Learning

1 citations · 2 across the 6 of their papers we have counts for

collaborators

8 papers

cs.IR2026

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…

cs.LG2026

Nemotron 3 Super: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning

NVIDIA, :, Aakshita Chandiramani +544

We describe the pre-training, post-training, and quantization of Nemotron 3 Super, a 120 billion (active 12 billion) parameter hybrid Mamba-Attention Mixture-of-Experts model. Nemo…

cs.IR2025

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.…

cs.IR2025

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…

cs.IR20251 cited

A Reproducibility Study of Product-side Fairness in Bundle Recommendation

Huy-Son Nguyen, Yuanna Liu, Masoud Mansoury +3

Recommender systems are known to exhibit fairness issues, particularly on the product side, where products and their associated suppliers receive unequal exposure in recommended re…

cs.IR2025

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…