12 papers
Leveraging Self-Paced Curriculum Learning for Enhanced Modality Balance in Multimodal Conversational Emotion Recognition
Phuong-Anh Nguyen, The-Son Le, Duc-Trong Le +1
Multimodal Emotion Recognition in Conversations (MERC) is a crucial task for understanding human interactions, where multimodal approaches integrating language, facial expressions,…
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…
BALM: A Model-Agnostic Framework for Balanced Multimodal Learning under Imbalanced Missing Rates
Phuong-Anh Nguyen, Tien Anh Pham, Duc-Trong Le +1
Learning from multiple modalities often suffers from imbalance, where information-rich modalities dominate optimization while weaker or partially missing modalities contribute less…
MissBench: Benchmarking Multimodal Affective Analysis under Imbalanced Missing Modalities
Tien Anh Pham, Phuong-Anh Nguyen, Duc-Trong Le +1
Multimodal affective computing underpins key tasks such as sentiment analysis and emotion recognition. Standard evaluations, however, often assume that textual, acoustic, and visua…
Divide and Refine: Enhancing Multimodal Representation and Explainability for Emotion Recognition in Conversation
Anh-Tuan Mai, Cam-Van Thi Nguyen, Duc-Trong Le
Multimodal emotion recognition in conversation (MERC) requires representations that effectively integrate signals from multiple modalities. These signals include modality-specific…
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.…