--- title: "Who cites PaperQA: Retrieval-Augmented — 57 citing papers" description: "57 papers of the Elamur Research library cite «PaperQA: Retrieval-Augmented Generative Agent for Scientific Research», found in their…" canonical: "https://research.elamur.ai/free/en/papers/lala-2023-paperqa-retrieval-augmented-generative/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/lala-2023-paperqa-retrieval-augmented-generative/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [PaperQA: Retrieval-Augmented Generative Agent for…](https://md.research.elamur.ai/free/en/papers/lala-2023-paperqa-retrieval-augmented-generative/) / cited by # Who cites «PaperQA: Retrieval-Augmented Generative Agent for Scientific Research» 57 papers of our library cite it (of the 149,439 whose bibliographies we read) · 15 with a page here, the most cited first · [← back to «PaperQA: Retrieval-Augmented Generative Agent for Scientific Research»](https://md.research.elamur.ai/free/en/papers/lala-2023-paperqa-retrieval-augmented-generative/) 1. [**Retrieval-Augmented Generation for Large Language Models: A Survey arXiv:2312.10997**Yunfan Gao, Yun Xiong, Xinyu Gao, et al.*2023 · 1,663 citations*](https://md.research.elamur.ai/free/en/papers/gao-2023-retrieval-augmented-generation-large-language/) 2. **[Benchmarking Retrieval-Augmented Generation for Medicine](https://md.research.elamur.ai/free/en/papers/xiong-2024-benchmarking-retrieval-augmented-generation-medicine/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Guangzhi Xiong, Qiao Jin, Zhiyong Lu, et al.*2024 · 430 citations* 3. [**A Review of Large Language Models and Autonomous Agents in Chemistry arXiv:2407.01603**Mayk Caldas Ramos, Christopher J. Collison, Andrew D. White*2024 · 288 citations*](https://md.research.elamur.ai/free/en/papers/ramos-2024-review-large-language-models-autonomous/) 4. **[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 · 246 citations* 5. [**Agent Laboratory: Using LLM Agents as Research Assistants arXiv:2501.04227**Samuel Schmidgall, Yusheng Su, Ze Wang, et al.*2025 · 139 citations*](https://md.research.elamur.ai/free/en/papers/schmidgall-2025-agent-laboratory-using-llm/) 6. [**The WMDP Benchmark: Measuring and Reducing Malicious Use With Unlearning arXiv:2403.03218**Nathaniel Li, Alexander Pan, Anjali Gopal, et al.*2024 · 127 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-wmdp-benchmark-measuring-reducing-malicious/) 7. [**Language agents achieve superhuman synthesis of scientific knowledge arXiv:2409.13740**Michael D. Skarlinski; Sam Cox; Jon M. Laurent; James D. Braza; Michaela Hinks; Michael J. Hammerling; Manvitha Ponnapati; Samuel G. Rodriques;, Andrew D. White*2024 · 89 citations*](https://md.research.elamur.ai/free/en/papers/skarlinski-2024-language-agents-achieve-superhuman/) 8. [**LAB-Bench: Measuring Capabilities of Language Models for Biology Research arXiv:2407.10362**Jon M. Laurent, Joseph D. Janizek, Michael Ruzo, et al.*2024 · 62 citations*](https://md.research.elamur.ai/free/en/papers/laurent-2024-lab-bench-measuring-capabilities/) 9. **[TC–RAG: Turing–Complete RAG's Case study on Medical LLM Systems](https://md.research.elamur.ai/free/en/papers/jiang-2025-tc-rag-turing-complete-rag/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinke Jiang, Yue Fang, Rihong Qiu, et al.*2025 · 25 citations* 10. **[AI4Research: A Survey of Artificial Intelligence for Scientific Research](https://md.research.elamur.ai/free/en/papers/chen-2025-ai4research-survey-artificial-intelligence/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Mingda Yang, Libo Qin, et al.*2025 · 21 citations* 11. **[PAPERMIND: Benchmarking Agentic Reasoning and Critique over Scientific Papers in Multimodal LLMs](https://md.research.elamur.ai/free/en/papers/zhao-2026-papermind-benchmarking-agentic-reasoning-critique/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yanjun Zhao, Tianxin Wei, Jiaru Zou, et al.*2026 · 2 citations* 12. **[A Binary Problem in Binary QA: Diverse LLMs or Diverse Question Interpretations? That Is the Ensembling Question](https://md.research.elamur.ai/free/en/papers/rosales-2026-binary-problem-binary-qa-diverse/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Rafael Rosales, Santiago Miret*2026* 13. **[Datasets for Scientific Literature Understanding: A Survey](https://md.research.elamur.ai/free/en/papers/zhang-2026-datasets-scientific-literature-understanding-survey/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuanzhe Zhang, Xun Zhao, Maodi Hu, et al.*2026* 14. **[IntrAgent: An LLM Agent for Content-Grounded Information Retrieval through Literature Review](https://md.research.elamur.ai/free/en/papers/ma-2026-intragent-llm-agent-content-grounded/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fengbo Ma, Zixin Rao, Xiaoting Li, et al.*2026* 15. **[TopoRAG: Graph-based RAG via Topology-aware Approximate Nearest Neighbor Search](https://md.research.elamur.ai/free/en/papers/wu-2026-toporag-graph-based-rag-topology/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tianhao Wu, Siqiang Luo*2026* 42 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/lala-2023-paperqa-retrieval-augmented-generative/) — PaperQA: Retrieval-Augmented Generative Agent for Scientific Research