Papers with biological grounding
NOSE: Neural Olfactory-Semantic Embedding with Tri-Modal Orthogonal Contrastive Learning (2026.acl-long)
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| Challenge: | Existing representation methods fail to fully capture olfactory pathway . current approaches focus on isolated segments of the olefactory pathways . |
| Approach: | They propose a representation learning framework that aligns molecular structure, receptor sequence, and natural language description. |
| Outcome: | The proposed framework achieves state-of-the-art and excellent zero-shot generalization . it decouples contributions of molecular structure, receptor sequence, and natural language description . |
LLM4Cell: Taxonomy and Evaluation of LLM and Agentic Models for Single-Cell Biology (2026.acl-long)
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Sajib Acharjee Dip, Adrika Zafor, Bikash Kumar Paul, Uddip Acharjee Shuvo, Muhit Islam Emon, Xuan Wang, Liqing Zhang
| Challenge: | Large language models are transforming biomedical discovery by linking molecular patterns with knowledge encoded in text. |
| Approach: | They propose to map 58 foundation and agentic models developed for single-cell research into eight key analytical tasks. |
| Outcome: | The proposed models are applied to eight key analytical tasks including annotation, trajectory inference, perturbation modeling, and drug-response prediction. |