collaborators

5 papers

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CL2026

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…

cs.CL2025

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…