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Biological function in RNA is encoded across scales, from local sequence motifs to long-range structural dependencies. Conventional RNA foundation models couple parameter capacity and inference depth within a fixed architecture, prescribing a fixed computation graph for each inference. Here we present Eco-RNA, an 80M-p...
DeconX transforms residual-based missing cell-type inference from exploratory analysis into a complete computational framework, enabling accurate characterization of tissue heterogeneity from archival bulk RNA-seq data even when single-cell references are incomplete.
CONDUIT, a training-free refresh policy that unifies single- and multi-image reuse as residual-stream restoration, is proposed, building on norm-weighted attention and an accessible pre-output cached-value-norm proxy, then applies empirical image-level relevance amplification before one global selection.
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