Multimodal contrastive learning using multilinear products is fragile to single bad modalities, and a gated version improves top-1 retrieval accuracy on synthetic and real trimodal data.
Contrasting with symile: Simple model-agnostic representation learning for unlimited modalities
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A zeta-like scaling law arises from power-law decay in data covariance spectra and signal projections, predicting when additional biomedical data improves model performance.
citing papers explorer
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Hidden in the Multiplicative Interaction: Uncovering Fragility in Multimodal Contrastive Learning
Multimodal contrastive learning using multilinear products is fragile to single bad modalities, and a gated version improves top-1 retrieval accuracy on synthetic and real trimodal data.
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How Much Data is Enough? The Zeta Law of Discoverability in Biomedical Data, featuring the enigmatic Riemann zeta function
A zeta-like scaling law arises from power-law decay in data covariance spectra and signal projections, predicting when additional biomedical data improves model performance.