CellTypeAgent: Trustworthy cell type annotation with Large Language Models
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Abstract (arXiv)
Cell type annotation is a critical yet laborious step in single-cell RNA sequencing analysis. We present a trustworthy large language model (LLM)-agent, CellTypeAgent, which integrates LLMs with verification from relevant databases. CellTypeAgent achieves higher accuracy than existing methods while mitigating hallucinations. We evaluated CellTypeAgent across nine real datasets involving 303 cell types from 36 tissues. This combined approach holds promise for more efficient and reliable cell type annotation.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 5 of its 18 references that are in the map. First posted on arXiv 13 May 2025.
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5 of 18 references.
References · 5
- 2023GPT-4 Technical Reportcited by 18,396
- 2025DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learningcited by 6,330
- 2023A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questionscited by 1,601
- 2023Privacy Issues in Large Language Models: A Surveycited by 60
- 2023Evaluating the Potential of Leading Large Language Models in Reasoning Biology Questionscited by 7
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