collaborators

6 papers

cs.AI2026

Deferred Audio Pruning with Local Audio-Visual Dynamics for Omni-LLMs

Kyeongyoon Lee, Hongyeob Kim, Youngeun Kim +1

Omni-modal LLMs jointly process audio, video, and text, but long multimodal sequences incur substantial prefill and KV-cache costs. Existing omni-modal compression methods primaril…

cs.CV2026

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.CV2026

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

DisCoRD: Discrete Tokens to Continuous Motion via Rectified Flow Decoding

Jungbin Cho, Junwan Kim, Jisoo Kim +5

Human motion is inherently continuous and dynamic, posing significant challenges for generative models. While discrete generation methods are widely used, they suffer from limited…

cs.CV2025

Question-Aware Gaussian Experts for Audio-Visual Question Answering

Hongyeob Kim, Inyoung Jung, Dayoon Suh +3

Audio-Visual Question Answering (AVQA) requires not only question-based multimodal reasoning but also precise temporal grounding to capture subtle dynamics for accurate prediction.…

cs.CV2025

RA-Touch: Retrieval-Augmented Touch Understanding with Enriched Visual Data

Yoorhim Cho, Hongyeob Kim, Semin Kim +3

Visuo-tactile perception aims to understand an object's tactile properties, such as texture, softness, and rigidity. However, the field remains underexplored because collecting tac…