arXiv Machine Learning June 10, 2026 By Konstantinos Kontras, Teodora Gagaleska, Thomas Strypsteen, Christos Chatzichristos, Matthew Blaschko, Maarten De Vos, Paul Pu Liang

SynIB: Informational Bottleneck for Maximizing Synergy in Multimodal Learning

Read the original on arXiv Machine Learning →

arXiv:2606. 09853v1 Announce Type: new Abstract: A central objective in multimodal learning is to capture synergy: task-relevant information that arises only from the joint use of multiple modalities, and is not available from any single modality alone.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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