arXiv: cs.AI preprintsInternational6 November 2026
Thalamus-Reasoning: A Multimodal Large Language Model for Multi-Sample Omics Reasoning
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arXiv:2605.06728v3 Announce Type: replace-cross Abstract: Large language models can reason over biological knowledge, but they are not naturally equipped to work with quantitative omics measurements. Existing approaches either convert expression profiles into long textual representations, often losing quantitative information, or connect omics encoders to language models for narrow tasks. We introduce Thalamus-Reasoning, a 9B multimodal language model that represents each bulk or single-cell transcriptome as a compact continuous embedding that can be interleaved with natural-language instructi
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