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20242026
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cs.CV2026

Real-Time Visual Attribution Streaming in Thinking Model

Seil Kang, Woojung Han, Junhyeok Kim +3

We present an amortized framework for real-time visual attribution streaming in multimodal thinking models. When these models generate code from a screenshot or solve math problems…

cs.CV2026

VisRef: Visual Refocusing while Thinking Improves Test-Time Scaling in Multi-Modal Large Reasoning Models

Soumya Suvra Ghosal, Youngeun Kim, Zhuowei Li +6

Advances in large reasoning models have shown strong performance on complex reasoning tasks by scaling test-time compute through extended reasoning. However, recent studies observe…

cs.CV2025

ZOO-Prune: Training-Free Token Pruning via Zeroth-Order Gradient Estimation in Vision-Language Models

Youngeun Kim, Youjia Zhang, Huiling Liu +3

Large Vision-Language Models (VLMs) enable strong multimodal reasoning but incur heavy inference costs from redundant visual tokens. Token pruning alleviates this issue, yet existi…

cs.CV2025

Backpropagation-Free Test-Time Adaptation via Probabilistic Gaussian Alignment

Youjia Zhang, Youngeun Kim, Young-Geun Choi +3

Test-time adaptation (TTA) enhances the zero-shot robustness under distribution shifts by leveraging unlabeled test data during inference. Despite notable advances, several challen…

cs.CV2024

Open-World Dynamic Prompt and Continual Visual Representation Learning

Youngeun Kim, Jun Fang, Qin Zhang +7

The open world is inherently dynamic, characterized by ever-evolving concepts and distributions. Continual learning (CL) in this dynamic open-world environment presents a significa…