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CliffRank trains two parallel predictors with mean squared error, a thresholded listwise loss, and Pairwise Preference Consistency (PPC), which aligns relative ordering in the preference-probability space, and defines its practical limits.
DISTAL is a dual-prior framework for structure-agnostic materials property prediction that combines self-supervised compositional pretraining with structure-aware knowledge distillation and achieves the strongest overall performance among all evaluated feature combinations.
Frequency-Domain Latent-attention Gated Pooling (FLaG), a plug-in aggregation module that re-expresses encoder outputs in the Fourier domain before final pooling, provides a transferable frequency-domain aggregation bias across protein, visual, and textual representations, with benefits that depend on the backbone and...
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