Tianjin University's Zhang Changqing introduces generalized multimodal fusion at CNCC 2026: from trustworthy evidence fusion to the Fusion Anything foundation model
At CNCC 2026, Tianjin University's Zhang Changqing presented the report "Generalized Multimodal Fusion Technology," introducing the team's research on multimodal representation, dynamic trustworthy fusion, and the general-purpose prediction foundation model Fusion Anything Model (FAM). The TMC method uses evidence theory to estimate uncertainty, raising crystal structure recognition accuracy from about 58%–59% to around 93.9%. FAM was tested on 18 real-world datasets, 12 modalities, and 11 types of prediction tasks, achieving an average accuracy about 6.9 percentage points higher than specialized fusion baselines.
At CNCC 2026, Tianjin University's Zhang Changqing presented the report "Generalized Multimodal Fusion Technology," introducing the team's research on multimodal representation, dynamic trustworthy fusion, and the general-purpose prediction foundation model Fusion Anything Model (FAM). The TMC method uses evidence theory to estimate uncertainty, raising crystal structure recognition accuracy from about 58%–59% to around 93.9%. FAM was tested on 18 real-world datasets, 12 modalities, and 11 types
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