3 citations · 4 across the 7 of their papers we have counts for
8 papers
A compact six-beam 3D magneto-optical trap based on multifunctional metasurface chips
Chen Qing, Huijie Sun, Yize Liu +5
Magneto-optical traps (MOTs), indispensable to cold-atom-based quantum computing and quantum precision measurement, are increasingly desired in compact and stable form. Particularl…
Look Before You Zoom: Adaptive Routing for the Resolution-Context Trade-off in Visual RAG
Oanh N. Tran, Thanh Quoc Hung Le, Oscar Chew +2
Vision-Language Models (VLMs) struggle as query-relevant objects become smaller. To address this, recent training-free approaches dynamically retrieve and zoom into local image reg…
Pop-Up Distractions Reveal Bag-of-Events Behavior in Video Large Language Models
Oscar Chew, Serhii Honcharenko, Qian-Hui Chen +4
A key capability for video understanding is reliably linking subjects to events across time, yet whether Video Large Language Models (VideoLLMs) actually achieve this remains uncle…
Is CLIP Cross-Eyed? Revealing and Mitigating Center Bias in the CLIP Family
Oscar Chew, Hsiao-Ying Huang, Kunal Jain +3
Recent research has shown that contrastive vision-language models such as CLIP often lack fine-grained understanding of visual content. While a growing body of work has sought to a…
PEPPER: Perception-Guided Perturbation for Robust Backdoor Defense in Text-to-Image Diffusion Models
Oscar Chew, Po-Yi Lu, Jayden Lin +2
Recent studies show that text-to-image (T2I) diffusion models are vulnerable to backdoor attacks, where a trigger in the input prompt can steer generation toward harmful or uninten…
The Role of Exploration Modules in Small Language Models for Knowledge Graph Question Answering
Yi-Jie Cheng, Oscar Chew, Yun-Nung Chen
Integrating knowledge graphs (KGs) into the reasoning processes of large language models (LLMs) has emerged as a promising approach to mitigate hallucination. However, existing wor…
Defending Text-to-image Diffusion Models: Surprising Efficacy of Textual Perturbations Against Backdoor Attacks
Oscar Chew, Po-Yi Lu, Jayden Lin +1
Text-to-image diffusion models have been widely adopted in real-world applications due to their ability to generate realistic images from textual descriptions. However, recent stud…
Understanding and Mitigating Spurious Correlations in Text Classification with Neighborhood Analysis
Oscar Chew, Hsuan-Tien Lin, Kai-Wei Chang +1
Recent research has revealed that machine learning models have a tendency to leverage spurious correlations that exist in the training set but may not hold true in general circumst…