mlsanityData to 7 Oct 2026

Large Language Models in Plant Biology

arXiv 2401.02789 ↗First posted 5 Jan 2024q-bio.GN cs.CLcited by 8

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Abstract (arXiv)

Large Language Models (LLMs), such as ChatGPT, have taken the world by storm and have passed certain forms of the Turing test. However, LLMs are not limited to human language and analyze sequential data, such as DNA, protein, and gene expression. The resulting foundation models can be repurposed to identify the complex patterns within the data, resulting in powerful, multi-purpose prediction tools able to explain cellular systems. This review outlines the different types of LLMs and showcases their recent uses in biology. Since LLMs have not yet been embraced by the plant community, we also cover how these models can be deployed for the plant kingdom.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 19 of its 77 references that are in the map. First posted on arXiv 5 Jan 2024.

Builds on

19 of 77 references.

References · 19

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7 more
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 6; 2026: 1.

8 papers.

  1. 2024ChemSafetyBench: Benchmarking LLM Safety on Chemistry Domaincited by 14
  2. 2025L-MTP: Leap Multi-Token Prediction Beyond Adjacent Context for Large Language Modelscited by 14
  3. 2025LLM4Cell: A Survey of Large Language and Agentic Models for Single-Cell Biologycited by 3
  4. 2025Foundation Models in Biomedical Imaging: Turning Hype into Realitycited by 2
  5. 2025ParaUni: Enhance Generation in Unified Multimodal Model with Reinforcement-driven Hierarchical Parallel Information Interactioncited by 1
  6. 2025Advancements in Weed Mapping: A Systematic Reviewcited by 0
  7. 2025MM-Telco: Benchmarks and Multimodal Large Language Models for Telecom Applicationscited by 0
  8. 2026WildIng: A Wildlife Image Invariant Representation Model for Geographical Domain Shiftcited by 0