165 lines
6.3 KiB
BibTeX
165 lines
6.3 KiB
BibTeX
% References for the IETF AI/agent landscape survey.
|
|
% Real, verifiable entries only. Agent-added entries must be checked.
|
|
|
|
% ── IETF / Standards quantitative analysis ────────────────────────────────
|
|
|
|
@inproceedings{mcquistin2021characterising,
|
|
author = {McQuistin, Stephen and Karan, Mladen and Khare, Prashant and
|
|
Perkins, Colin and Tyson, Gareth and Purver, Matthew and
|
|
Healey, Patrick and Iqbal, Waleed and Qadir, Junaid and
|
|
Castro, Ignacio},
|
|
title = {Characterising the {IETF} Through the Lens of {RFC} Deployment},
|
|
booktitle = {Proceedings of the 21st ACM Internet Measurement Conference
|
|
({IMC} '21)},
|
|
year = {2021},
|
|
pages = {137--149},
|
|
doi = {10.1145/3487552.3487821},
|
|
isbn = {9781450391290},
|
|
}
|
|
|
|
@inproceedings{zhang2025affiliations,
|
|
author = {Zhang, Yangjun and McQuistin, Stephen and Karan, Mladen and
|
|
Ramirez-Centeno, Hugo Enrique and Perkins, Colin and
|
|
Tyson, Gareth and Castro, Ignacio},
|
|
title = {Two Decades of {IETF} Affiliations: Evolution and Impact},
|
|
booktitle = {Proceedings of the 2025 Applied Networking Research Workshop
|
|
({ANRW} '25)},
|
|
year = {2025},
|
|
doi = {10.1145/3744200.3744757},
|
|
}
|
|
|
|
@techreport{tenoever2022aid,
|
|
author = {ten Oever, Niels and Cath, Corinne and K{\"u}hlewind, Mirja
|
|
and Perkins, Colin S.},
|
|
title = {Report from the {IAB} Workshop on Analyzing {IETF} Data
|
|
({AID}) 2021},
|
|
institution = {Internet Architecture Board},
|
|
type = {RFC},
|
|
number = {9307},
|
|
year = {2022},
|
|
month = sep,
|
|
issn = {2070-1721},
|
|
note = {Informational},
|
|
doi = {10.17487/RFC9307},
|
|
}
|
|
|
|
@misc{jimenez2024automating,
|
|
author = {Jim{\'e}nez, Jaime},
|
|
title = {Automating {IETF} Insights Generation with {AI}},
|
|
year = {2024},
|
|
eprint = {2410.13301},
|
|
archivePrefix = {arXiv},
|
|
primaryClass = {cs.NI},
|
|
}
|
|
|
|
% ── LLM-assisted annotation / classification ──────────────────────────────
|
|
|
|
@article{gilardi2023chatgpt,
|
|
author = {Gilardi, Fabrizio and Alizadeh, Meysam and Kubli, Ma{\"e}l},
|
|
title = {{ChatGPT} Outperforms Crowd-Workers for Text-Annotation Tasks},
|
|
journal = {Proceedings of the National Academy of Sciences},
|
|
year = {2023},
|
|
volume = {120},
|
|
number = {30},
|
|
pages = {e2305016120},
|
|
doi = {10.1073/pnas.2305016120},
|
|
}
|
|
|
|
@inproceedings{tan2024survey,
|
|
author = {Tan, Zhen and Li, Dawei and Wang, Song and Beigi, Alimohammad
|
|
and Jiang, Bohan and Bhattacharjee, Amrita and Karami,
|
|
Mansooreh and Li, Jundong and Cheng, Lu and Liu, Huan},
|
|
title = {Large Language Models for Data Annotation and Synthesis:
|
|
{A} Survey},
|
|
booktitle = {Proceedings of the 2024 Conference on Empirical Methods in
|
|
Natural Language Processing ({EMNLP} 2024)},
|
|
year = {2024},
|
|
pages = {930--957},
|
|
address = {Miami, Florida, USA},
|
|
doi = {10.18653/v1/2024.emnlp-main.54},
|
|
}
|
|
|
|
@misc{yang2025agentprotocols,
|
|
author = {Yang, Yingxuan and Chai, Huacan and Song, Yuanyi and
|
|
Qi, Siyuan and Wen, Muning and Li, Ning and Liao, Junwei
|
|
and Hu, Haoyi and Lin, Jianghao and Chang, Gaowei and
|
|
Liu, Weiwen and Wen, Ying and Yu, Yong and Zhang, Weinan},
|
|
title = {A Survey of {AI} Agent Protocols},
|
|
year = {2025},
|
|
eprint = {2504.16736},
|
|
archivePrefix = {arXiv},
|
|
primaryClass = {cs.AI},
|
|
}
|
|
|
|
% ── Inter-rater reliability of LLM labels ─────────────────────────────────
|
|
|
|
@misc{reiss2023reliability,
|
|
author = {Reiss, Michael V.},
|
|
title = {Testing the Reliability of {ChatGPT} for Text Annotation
|
|
and Classification: {A} Cautionary Remark},
|
|
year = {2023},
|
|
eprint = {2304.11085},
|
|
archivePrefix = {arXiv},
|
|
primaryClass = {cs.CL},
|
|
}
|
|
|
|
@inproceedings{wang2023nlgeval,
|
|
author = {Wang, Jiaan and Liang, Yunlong and Meng, Fandong and
|
|
Sun, Zengkui and Shi, Haoxiang and Li, Zhixu and Xu, Jinan
|
|
and Qu, Jianfeng and Zhou, Jie},
|
|
title = {Is {ChatGPT} a Good {NLG} Evaluator? {A} Preliminary Study},
|
|
booktitle = {Proceedings of the 4th Workshop on New Frontiers in
|
|
Summarization ({NewSumm@EMNLP} 2023)},
|
|
year = {2023},
|
|
note = {arXiv:2303.04048},
|
|
}
|
|
|
|
% ── Cohen's kappa / Landis-Koch (methodological) ──────────────────────────
|
|
|
|
@article{cohen1960kappa,
|
|
author = {Cohen, Jacob},
|
|
title = {A Coefficient of Agreement for Nominal Scales},
|
|
journal = {Educational and Psychological Measurement},
|
|
year = {1960},
|
|
volume = {20},
|
|
number = {1},
|
|
pages = {37--46},
|
|
doi = {10.1177/001316446002000104},
|
|
}
|
|
|
|
@article{landis1977kappa,
|
|
author = {Landis, J. Richard and Koch, Gary G.},
|
|
title = {The Measurement of Observer Agreement for Categorical Data},
|
|
journal = {Biometrics},
|
|
year = {1977},
|
|
volume = {33},
|
|
number = {1},
|
|
pages = {159--174},
|
|
doi = {10.2307/2529310},
|
|
}
|
|
|
|
% ── Text embeddings / semantic similarity ─────────────────────────────────
|
|
|
|
@inproceedings{reimers2019sbert,
|
|
author = {Reimers, Nils and Gurevych, Iryna},
|
|
title = {Sentence-{BERT}: Sentence Embeddings using Siamese {BERT}-Networks},
|
|
booktitle = {Proceedings of the 2019 Conference on Empirical Methods in
|
|
Natural Language Processing and the 9th International Joint
|
|
Conference on Natural Language Processing
|
|
({EMNLP-IJCNLP} 2019)},
|
|
year = {2019},
|
|
pages = {3982--3992},
|
|
doi = {10.18653/v1/D19-1410},
|
|
}
|
|
|
|
@misc{nussbaum2024nomic,
|
|
author = {Nussbaum, Zach and Morris, John X. and Duderstadt, Brandon
|
|
and Mulyar, Andriy},
|
|
title = {Nomic Embed: Training a Reproducible Long Context Text
|
|
Embedder},
|
|
year = {2024},
|
|
eprint = {2402.01613},
|
|
archivePrefix = {arXiv},
|
|
primaryClass = {cs.CL},
|
|
}
|