---
title: "Who cites AutoML in the Age of Large — 17 citing papers"
description: "17 papers of the Elamur Research library cite «AutoML in the Age of Large Language Models: Current Challenges, Future Opportunities and…"
canonical: "https://research.elamur.ai/free/en/papers/tornede-2023-automl-age-large-language-models/cited-by/"
---
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# Who cites «AutoML in the Age of Large Language Models: Current Challenges, Future Opportunities and Risks»

17 papers of our library cite it (of the 149,439 whose bibliographies we read) · 8 with a page here, the most cited first · [← back to «AutoML in the Age of Large Language Models: Current Challenges, Future Opportunities and Risks»](https://md.research.elamur.ai/free/en/papers/tornede-2023-automl-age-large-language-models/)

1. **[Security and Privacy Challenges of Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/das-2024-security-privacy-challenges-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Badhan Chandra Das, M. Hadi Amini, Yanzhao Wu*2024 · 424 citations*
2. [**Challenges and Applications of Large Language Models arXiv:2307.10169**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 301 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/)
3. **[Towards Efficient Generative Large Language Model Serving: A Survey from Algorithms to Systems](https://md.research.elamur.ai/free/en/papers/miao-2023-towards-efficient-generative-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Xupeng Miao, Gabriele Oliaro, Zhihao Zhang, et al.*2023 · 110 citations*
4. [**MLGym: A New Framework and Benchmark for Advancing AI Research Agents arXiv:2502.14499**Deepak Nathani, Lovish Madaan, Nicholas Roberts, et al.*2025 · 50 citations*](https://md.research.elamur.ai/free/en/papers/nathani-2025-mlgym-new-framework-benchmark/)
5. [**RE-Bench: Evaluating frontier AI R&D capabilities of language model agents against human experts arXiv:2411.15114**Hjalmar Wijk, Tao Lin, Joel Becker, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/wijk-2024-re-bench-evaluating-frontier/)
6. [**AgentRxiv: Towards Collaborative Autonomous Research arXiv:2503.18102**Samuel Schmidgall, Michael Moor*2025 · 39 citations*](https://md.research.elamur.ai/free/en/papers/schmidgall-2025-agentrxiv-collaborative-autonomous-research/)
7. **[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*
8. **[A2O: LLM-based Agentic Learning of Action-to-Object Features for Video Action Recognition](https://md.research.elamur.ai/free/en/papers/sekii-2026-a2o-llm-based-agentic-learning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Taiki Sekii, Fumiaki Sato*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/tornede-2023-automl-age-large-language-models/) — AutoML in the Age of Large Language Models: Current Challenges, Future Opportunities and Risks