arXiv Machine Learning
techCenter
Mitigating Strong-Modality Collapse in Multimodal Learning via Inverted Asymmetric Fusiontranslating…
1 min readUnknownarXiv Digital Media
arXiv:2608.26879v1 Announce Type: new
Abstract: Fusing multiple modalities is expected to improve model performance. However, on the MultiHuSE dataset, early, late, and symmetric attention fusion often fail to outperform the best unimodal baseline (text). Pathway isolation of a…