Screening of 52,000 bioRxiv preprints finds dual-use-adjacent content routinely present in open titles and abstracts, often exceeding risk thresholds.
Interpretable
5 Pith papers cite this work. Polarity classification is still indexing.
5
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
verdicts
UNVERDICTED 5roles
background 1polarities
background 1representative citing papers
GoForth is a forward-trained encoder-decoder RNA language model that generates sequences under mixed constraints on fold, sequence, and coding by separating sequence prior, forward folding sampler, and reward oracle.
Post-training stages reshape generalization in biological reasoning models distinctly: CPT aligns with biological language, SFT boosts ID performance but causes OOD to peak early and decline, while RL on strong SFT checkpoints can recover OOD generalization.
TadA-Bench supplies a chronological million-variant wet-lab replay benchmark from 31 TadA directed-evolution rounds that evaluates models on future-round variant ranking given only earlier data.
This review surveys current machine learning methods for RNA secondary structure prediction, identifies a generalization crisis prompting homology-aware benchmarking, and outlines future challenges including pseudoknots, long transcripts, modified nucleotides, and dynamic ensembles.
citing papers explorer
-
How Post-Training Shapes Biological Reasoning Models
Post-training stages reshape generalization in biological reasoning models distinctly: CPT aligns with biological language, SFT boosts ID performance but causes OOD to peak early and decline, while RL on strong SFT checkpoints can recover OOD generalization.