---
title: "Who cites GeneGPT: Augmenting Large — 48 citing papers"
description: "48 papers of the Elamur Research library cite «GeneGPT: Augmenting Large Language Models with Domain Tools for Improved Access to…"
canonical: "https://research.elamur.ai/free/en/papers/jin-2023-genegpt-augmenting-large-language-models/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/jin-2023-genegpt-augmenting-large-language-models/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [GeneGPT: Augmenting Large Language Models with…](https://md.research.elamur.ai/free/en/papers/jin-2023-genegpt-augmenting-large-language-models/) / cited by

# Who cites «GeneGPT: Augmenting Large Language Models with Domain Tools for Improved Access to Biomedical Information»

48 papers of our library cite it (of the 141,840 whose bibliographies we read) · 7 with a page here, the most cited first · [← back to «GeneGPT: Augmenting Large Language Models with Domain Tools for Improved Access to Biomedical Information»](https://md.research.elamur.ai/free/en/papers/jin-2023-genegpt-augmenting-large-language-models/)

1. [**ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs arXiv:2307.16789**Yujia Qin, Shihao Liang, Yining Ye, et al.*2023 · 566 citations*](https://md.research.elamur.ai/free/en/papers/qin-2023-toolllm-facilitating-large-language-models/)
2. **[MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoning](https://md.research.elamur.ai/free/en/papers/tang-2024-medagents-large-language-models-as/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiangru Tang, Anni Zou, Zhuosheng Zhang, et al.*2024 · 245 citations*
3. [**Evaluating Large Language Models: A Comprehensive Survey arXiv:2310.19736**Zishan Guo, Renren Jin, Chuang Liu, et al.*2023 · 178 citations*](https://md.research.elamur.ai/free/en/papers/guo-2023-evaluating-large-language-models-comprehensive/)
4. **[ToolQA: A Dataset for LLM Question Answering with External Tools](https://md.research.elamur.ai/free/en/papers/zhuang-2023-toolqa-dataset-llm-question-answering/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuchen Zhuang, Yue Yu, Kuan Wang, et al.*2023 · 177 citations*
5. [**Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity arXiv:2310.07521**Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.*2023 · 170 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-survey-factuality-large-language-models/)
6. **[ToolkenGPT: Augmenting Frozen Language Models with Massive Tools via Tool Embeddings](https://md.research.elamur.ai/free/en/papers/hao-2023-toolkengpt-augmenting-frozen-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shibo Hao, Tianyang Liu, Zhen Wang, et al.*2023 · 142 citations*
7. [**Survey of Tool Use in Large Language Models (大语言模型的工具使用综述) Acta Automatica Sinica (自动化学报)**Yining Zheng (郑逸宁), Zhen Yu (余镇), Bufan Li (李不凡), et al.*2025*](https://md.research.elamur.ai/free/en/papers/zheng-2025-tool-use-large/)

41 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/jin-2023-genegpt-augmenting-large-language-models/) — GeneGPT: Augmenting Large Language Models with Domain Tools for Improved Access to Biomedical Information