LLM4Cell: Taxonomy and Evaluation of LLM and Agentic Models for Single-Cell Biology
Published:
LLM4Cell organizes foundation and agentic models for single-cell research across model families, data modalities, analytical tasks, datasets, and evaluation dimensions. The paper identifies gaps in biological grounding, standardization, interpretability, and trustworthy evaluation.
ACL 2026 (Main) Paper
@inproceedings{dip2026llm4cell,
title = {LLM4Cell: Taxonomy and Evaluation of LLM and Agentic Models for Single-Cell Biology},
author = {Dip, Sajib Acharjee and Zafor, Adrika and Paul, Bikash Kumar and Shuvo, Uddip Acharjee and Emon, Muhit Islam and Wang, Xuan and Zhang, Liqing},
booktitle = {Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
pages = {41913--41954},
year = {2026},
publisher = {Association for Computational Linguistics},
doi = {10.18653/v1/2026.acl-long.1942}
}