15 papers
SCENARIODIFF: A Scenario-level Guidance Framework for Multimodal Time Series Forecasting--Extended Version
Tuan-Binh Tran, Dat Nguyen Cong, Duc-Trong Le +2
Textual context such as news, reports, and logs can provide valuable signals for time series forecasting, especially when future dynamics are driven by external events that are not…
PGE-SAM: Prompt-Guided Feature Enhancement for Interactive Segmentation under Degradation
Tuan-Duc Nguyen, Anh-Tuan Mai, Duc-Trong Le
Segment Anything Model (SAM) has revolutionized promptable image segmentation with strong zero-shot generalization. However, its performance degrades substantially under real-world…
FR-DETR: Frequency and Recurrent Feature Refinement for Robust Object Detection under Adverse Weather
Tuan-Duc Nguyen, Duc-Trong Le
Object detection under adverse weather remains challenging due to severe visual degradations and domain shifts. Existing enhancer-based approaches attempt to improve detection by c…
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…
VoteGCL: Enhancing Graph-based Recommendations with Majority-Voting LLM-Rerank Augmentation
Minh-Anh Nguyen, Bao Nguyen, Ha Lan N. T. +3
Recommendation systems often suffer from data sparsity caused by limited user-item interactions, which degrade their performance and amplify popularity bias in real-world scenarios…
CLEAR: Causal Learning Framework For Robust Histopathology Tumor Detection Under Out-Of-Distribution Shifts
Kieu-Anh Truong Thi, Huy-Hieu Pham, Duc-Trong Le
Domain shift in histopathology, often caused by differences in acquisition processes or data sources, poses a major challenge to the generalization ability of deep learning models.…