10 citations · 26 across the 14 of their papers we have counts for
4 papers · 1 filter
Multi-Modal Continual Learning via Cross-Modality Adapters and Representation Alignment with Knowledge Preservation
Evelyn Chee, Wynne Hsu, Mong Li Lee
Continual learning is essential for adapting models to new tasks while retaining previously acquired knowledge. While existing approaches predominantly focus on uni-modal data, mul…
Test-Time Adaptation by Causal Trimming
Yingnan Liu, Rui Qiao, Mong Li Lee +1
Test-time adaptation aims to improve model robustness under distribution shifts by adapting models with access to unlabeled target samples. A primary cause of performance degradati…
Towards Fully Interpretable Deep Neural Networks: Are We There Yet?
Sandareka Wickramanayake, Wynne Hsu, Mong Li Lee
Despite the remarkable performance, Deep Neural Networks (DNNs) behave as black-boxes hindering user trust in Artificial Intelligence (AI) systems. Research on opening black-box DN…
Towards Maximizing the Representation Gap between In-Domain & Out-of-Distribution Examples
Jay Nandy, Wynne Hsu, Mong Li Lee
Among existing uncertainty estimation approaches, Dirichlet Prior Network (DPN) distinctly models different predictive uncertainty types. However, for in-domain examples with high…