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Following is the list of the most popular NAS benchmarks:
# NAS-Bench-101 <ref>Ying, C., Klein, A., Christiansen, E., Real, E., Murphy, K., & Hutter, F. (2019, May). Nas-bench-101: Towards reproducible neural architecture search. In International Conference on Machine Learning (pp. 7105-7114). PMLR.</ref>
# NAS-Bench-201 <ref>Dong, X., & Yang, Y. (2020). Nas-bench-201: Extending the scope of reproducible neural architecture search. arXiv preprint arXiv:2001.00326.</ref>
# NAS-Bench-1shot1<ref>Zela, A., Siems, J., & Hutter, F. (2020). Nas-bench-1shot1: Benchmarking and dissecting one-shot neural architecture search. arXiv preprint arXiv:2001.10422.</ref>
# NAS-Bench-301 <ref>Siems, J., Zimmer, L., Zela, A., Lukasik, J., Keuper, M. and Hutter, F., 2020. Nas-bench-301 and the case for surrogate benchmarks for neural architecture search. arXiv preprint arXiv:2008.09777.</ref>
# NAS-Bench-ASR <ref>Mehrotra, A., Ramos, A. G. C., Bhattacharya, S., Dudziak, Ł., Vipperla, R., Chau, T., ... & Lane, N. D. (2020, September). Nas-bench-asr: Reproducible neural architecture search for speech recognition. In International Conference on Learning Representations.</ref>
# NAS-Bench-NLP<ref>Klyuchnikov, N., Trofimov, I., Artemova, E., Salnikov, M., Fedorov, M., & Burnaev, E. (2020). NAS-Bench-NLP: neural architecture search benchmark for natural language processing. arXiv preprint arXiv:2006.07116.</ref>
# TransNAS-Bench-101
# LC-Bench <ref>Zimmer, L., Lindauer, M., & Hutter, F. (2021). Auto-Pytorch: multi-fidelity metalearning for efficient and robust autoDL. IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(9), 3079-3090.</ref>
# NAS-Bench-x11 <ref>Yan, S., White, C., Savani, Y., & Hutter, F. (2021). NAS-Bench-x11 and the Power of Learning Curves. Advances in Neural Information Processing Systems, 34.</ref>
# NAS-Bench-Suite<ref>Mehta, Y., White, C., Zela, A., Krishnakumar, A., Zabergja, G., Moradian, S., ... & Hutter, F. (2022). NAS-Bench-Suite: NAS Evaluation is (Now) Surprisingly Easy. arXiv preprint arXiv:2201.13396.</ref>
# HW-NAS-Bench <ref>Li, C., Yu, Z., Fu, Y., Zhang, Y., Zhao, Y., You, H., ... & Lin, Y. (2021). HW-NAS-Bench: Hardware-aware neural architecture search benchmark. arXiv preprint arXiv:2103.10584.</ref>
==See also==
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