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HaoTian Ni

2 accepted papers

2026

Information-Theoretic Decomposition for Multimodal Interaction Learning

CVPR 2026

Multimodal learning hinges on capturing redundant, unique, and synergistic information across modalities, which collectively constitute multimodal interactions. A critical yet underexplored challenge is that these implicit interactions vary dynamically across samples. In this work, we present the fi

Cited by 0SourcecodeScholar
2025

RollingQ: Reviving the Cooperation Dynamics in Multimodal Transformer

ICML 2025poster

Multimodal learning faces challenges in effectively fusing information from diverse modalities, especially when modality quality varies across samples. Dynamic fusion strategies, such as attention mechanism in Transformers, aim to address such challenge by adaptively emphasizing modalities based on…