LOGICA adds context to pretrained biological LMs via logit-space contrastive alignment with gated adapters, improving AUC on held-out drug-resistance mutation ranking from ~0.55 to ~0.65 while preserving token likelihoods.
DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome
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A KL-divergence metric on inter-motif distance distributions in a centeny representation ranks the accuracy of human T2T genome assemblies at centromeres.
The Stakeholder Grounding Exercise shows neural text embeddings are 19-26pp less reliable than human experts at capturing semantic distinctions, with misalignment strongly correlated to poorer clustering performance (ρ=0.9), replicated across Danish policy and US AI domains.
citing papers explorer
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Contextualizing Biological Language Models across Modalities via Logit-Space Contrastive Alignment
LOGICA adds context to pretrained biological LMs via logit-space contrastive alignment with gated adapters, improving AUC on held-out drug-resistance mutation ranking from ~0.55 to ~0.65 while preserving token likelihoods.
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A mathematical framework for centromere-aware evaluation of human genome assemblies
A KL-divergence metric on inter-motif distance distributions in a centeny representation ranks the accuracy of human T2T genome assemblies at centromeres.
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Grounding Text Embeddings in Stakeholder Associations
The Stakeholder Grounding Exercise shows neural text embeddings are 19-26pp less reliable than human experts at capturing semantic distinctions, with misalignment strongly correlated to poorer clustering performance (ρ=0.9), replicated across Danish policy and US AI domains.