Author

Youngchae Chee

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#artificial intelligence Jan 2026

MAD: Modality-Adaptive Decoding for Mitigating Cross-Modal Hallucinations in Multimodal Large Language Models

This work proposes Modality-Adaptive Decoding (MAD), a training-free method that adaptively weights modality-specific decoding branches based on task requirements based on task requirements, demonstrating that explicit modality awareness through self-assessment is crucial for robust multimodal reasoning.

Sangyun Chung, Se Yeon Kim, Youngchae Chee et al. · arXiv.org · 3 citations · ⚡2

#artificial intelligence Preprint Aug 2026

PRISM: Predictive Recomposition via Semantic Latent Decomposition for View-invariant Video Representation Learning

This work decomposes video into view-invariant and view-variant latents and recompose them under language supervision encouraging clean decomposition of the two streams, and proposes PRISM, that achieves state-of-the-art results on EgoExo4D, EgoExoLearn, AE2, even surpassing in-domain models under zero-shot setting.

Youngchae Chee, Ho-Su Lee, Sungjune Park et al. · 0 citations