mlsanityData to 14 Oct 2026

LLM4Cell: A Survey of Large Language and Agentic Models for Single-Cell Biology

arXiv 2510.07793 ↗First posted 9 Oct 2025cs.CL cs.AIcited by 3

On the map: LLM agents and tool use → Medical and scientific domain agents

Abstract (arXiv)

Large language models (LLMs) and emerging agentic frameworks are beginning to transform single-cell biology by enabling natural-language reasoning, generative annotation, and multimodal data integration. However, progress remains fragmented across data modalities, architectures, and evaluation standards. LLM4Cell presents the first unified survey of 58 foundation and agentic models developed for single-cell research, spanning RNA, ATAC, multi-omic, and spatial modalities. We categorize these methods into five families-foundation, text-bridge, spatial, multimodal, epigenomic, and agentic-and map them to eight key analytical tasks including annotation, trajectory and perturbation modeling, and drug-response prediction. Drawing on over 40 public datasets, we analyze benchmark suitability, data diversity, and ethical or scalability constraints, and evaluate models across 10 domain dimensions covering biological grounding, multi-omics alignment, fairness, privacy, and explainability. By linking datasets, models, and evaluation domains, LLM4Cell provides the first integrated view of language-driven single-cell intelligence and outlines open challenges in interpretability, standardization, and trustworthy model development.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Placed in Medical and scientific domain agents, one of 16 directions in LLM agents and tool use. Builds on 13 of its 35 references that are in the map. First posted on arXiv 9 Oct 2025.

Builds on

13 of 35 references.

References · 13

  1. 2023Using an LLM to Help With Code Understandingcited by 228
  2. 2023Large-Scale Cell Representation Learning via Divide-and-Conquer Contrastive Learningcited by 11
  3. 2024Large Language Models in Plant Biologycited by 8
  4. 2025scAgent: Universal Single-Cell Annotation via a LLM Agentcited by 5
  5. 2025GeneMamba: An Efficient and Effective Foundation Model on Single Cell Datacited by 5
  6. 2025CellVerse: Do Large Language Models Really Understand Cell Biology?cited by 5
  7. 2024ChatCell: Facilitating Single-Cell Analysis with Natural Languagecited by 3
  8. 2024scRDiT: Generating single-cell RNA-seq data by diffusion transformers and accelerating samplingcited by 3
  9. 2024QuST-LLM: Integrating Large Language Models for Comprehensive Spatial Transcriptomics Analysiscited by 3
  10. 2025scMamba: A Scalable Foundation Model for Single-Cell Multi-Omics Integration Beyond Highly Variable Feature Selectioncited by 3
  11. 2025Spatial Coordinates as a Cell Language: A Multi-Sentence Framework for Imaging Mass Cytometry Analysiscited by 2
  12. 2025Cell2Text: Multimodal LLM for Generating Single-Cell Descriptions from RNA-Seq Datacited by 2
1 more
  1. 2025Towards Applying Large Language Models to Complement Single-Cell Foundation Modelscited by 1

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 3.

3 papers.

  1. 2026ES-Merging: Biological MLLM Merging via Embedding Space Signalscited by 0
  2. 2026scLLM-DSC: LLM-Knowledge Enhanced Cross-Modal Deep Structural Clustering for Single-Cell RNA Sequencingcited by 0
  3. 2026Stable-Shift: Biologically Structured Prediction of Transcriptional Responses to Unseen Gene Perturbationscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024Single-Cell Omics Arena: A Benchmark Study for Large Language Models on Cell Type Annotation Using Single-Cell Data
  2. 2026SC-Arena: A Natural Language Benchmark for Single-Cell Reasoning with Knowledge-Augmented Evaluation
  3. 2026scPilot: Large Language Model Reasoning Toward Automated Single-Cell Analysis and Discovery
  4. 2026The limits of bio-molecular modeling with large language models : a cross-scale evaluation
  5. 2026Open World Knowledge Aided Single-Cell Foundation Model with Robust Cross-Modal Cell-Language Pre-training
  6. 2025Cell-o1: Training LLMs to Solve Single-Cell Reasoning Puzzles with Reinforcement Learning
  7. 2025ReCellTy: Domain-Specific Knowledge Graph Retrieval-Augmented LLMs Reasoning Workflow for Single-Cell Annotation
  8. 2024LAB-Bench: Measuring Capabilities of Language Models for Biology Research