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Communication network engineering in enterprise environments is traditionally a complex, time-consuming, and error-prone manual process.
R. Beckett, R. Mahajan, T. Millstein, J. Padhye, and D. Walker, “Don’t mind the gap: Bridging network-wide objectives and device-level configurations,” in Proceedings of the 2016 ACM SIGCOMM Conference , 2016, pp. 328–341
2016
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P. Lewis, E. Perez, A. Piktus, F. Petroni, V. Karpukhin, N. Goyal, H. Küttler, M. Lewis, W.-t. Yih, T. Rocktäschel et al. , “Retrieval-augmented generation for knowledge-intensive nlp tasks,” Advances in Neural Information Processing Systems , vol. 33, pp. 9459–9474, 2020
2020
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A. S. Jacobs, R. J. Pfitscher, R. H. Ribeiro, R. A. Ferreira, L. Z. Granville, W. Willinger, and S. G. Rao, “Hey, lumi! using natural language for { \{ intent-based } \} network management,” in USENIX ATC 21 , 2021, pp. 625–639
2021
Earlier work this paper cites.
Z. B. Houidi and D. Rossi, “Neural language models for network configuration: Opportunities and reality check,” Computer Communications , vol. 193, pp. 118–125, 2022
2022
Earlier work this paper cites.
A. Leivadeas and M. Falkner, “A survey on intent based networking,” IEEE Communications Surveys & Tutorials , 2022
2022
Earlier work this paper cites.
H. Chen, Y. Miao, L. Chen, H. Sun, H. Xu, L. Liu, G. Zhang, and W. Wang, “Software-defined network assimilation: bridging the last mile towards centralized network configuration management with nassim,” in Proceedings of the ACM SIGCOMM 2022 Conference , 2022, pp. 281–297
2022
Cited alongside, same era.
J. Wei, X. Wang, D. Schuurmans, M. Bosma, F. Xia, E. Chi, Q. V. Le, D. Zhou et al. , “Chain-of-thought prompting elicits reasoning in large language models,” Advances in neural information processing systems , vol. 35, pp. 24 824–24 837, 2022
2022
Cited alongside, same era.
Z. Guo, F. Li, J. Shen, T. Xie, S. Jiang, and X. Wang, “Configreco: Network configuration recommendation with graph neural networks,” IEEE Network , 2023
2023
Cited alongside, same era.
J. Zhao, H. Sun, J. Wang, Q. Qi, Z. Zhuang, S. Tao, and J. Liao, “Confpilot: A pilot for faster configuration by learning from device manuals,” in 2023 IEEE 43rd International Conference on Distributed Computing Systems (ICDCS) . IEEE, 2023, pp. 108–119
2023
Later among the works it cites.
C. Wang, M. Scazzariello, A. Farshin, S. Ferlin, D. Kostić, and M. Chiesa, “Netconfeval: Can llms facilitate network configuration?” Proceedings of the ACM on Networking , vol. 2, pp. 1–25, 2024
2024
Closest in time.
D. Donadel, F. Marchiori, L. Pajola, and M. Conti, “Can llms understand computer networks? towards a virtual system administrator,” 2024
2024
Closest in time.
C.-N. Hang, P.-D. Yu, R. Morabito, and C.-W. Tan, “Large language models meet next-generation networking technologies: A review,” Future Internet , vol. 16, p. 365, 2024
2024
Closest in time.
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2023
Cited alongside, same era.
S. E. Ooi, R. Beuran, T. Kuroda, T. Kuwahara, R. Hotchi, N. Fujita, and Y. Tan, “Intent-driven secure system design: Methodology and implementation,” Computers & Security , vol. 124, 2023
2023
Cited alongside, same era.