activity
20222026
most citedQuantifying and Enhancing Multi-modal Robustness with Modality Preference

4 citations · 6 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2026

Information-Theoretic Decomposition for Multimodal Interaction Learning

Zequn Yang, Yake Wei, Haotian Ni +2

Multimodal learning hinges on capturing redundant, unique, and synergistic information across modalities, which collectively constitute multimodal interactions. A critical yet unde…

cs.CV2026

MIBench: Evaluating LMMs on Multimodal Interaction

Yu Miao, Zequn Yang, Yake Wei +5

In different multimodal scenarios, it needs to integrate and utilize information across modalities in a specific way based on the demands of the task. Different integration ways be…

cs.LG2025

Efficient Quantification of Multimodal Interaction at Sample Level

Zequn Yang, Hongfa Wang, Di Hu

Interactions between modalities -- redundancy, uniqueness, and synergy -- collectively determine the composition of multimodal information. Understanding these interactions is cruc…

cs.LG2025

Adaptive Unimodal Regulation for Balanced Multimodal Information Acquisition

Chengxiang Huang, Yake Wei, Zequn Yang +1

Sensory training during the early ages is vital for human development. Inspired by this cognitive phenomenon, we observe that the early training stage is also important for the mul…

cs.CV2024★ 4 cited

Quantifying and Enhancing Multi-modal Robustness with Modality Preference

Zequn Yang, Yake Wei, Ce Liang +1

Multi-modal models have shown a promising capability to effectively integrate information from various sources, yet meanwhile, they are found vulnerable to pervasive perturbations,…

cs.CV2022★ 2 cited

Reasoning with Multi-Structure Commonsense Knowledge in Visual Dialog

Shunyu Zhang, Xiaoze Jiang, Zequn Yang +2

Visual Dialog requires an agent to engage in a conversation with humans grounded in an image. Many studies on Visual Dialog focus on the understanding of the dialog history or the…