Toward Reproducing Network Research Results Using Large Language Models

Author:

Xiang Qiao1ORCID,Lin Yuling1ORCID,Fang Mingjun1ORCID,Huang Bang1ORCID,Huang Siyong1ORCID,Wen Ridi1ORCID,Le Franck2ORCID,Kong Linghe3ORCID,Shu Jiwu4ORCID

Affiliation:

1. Xiamen University

2. IBM Research

3. Shanghai Jiao Tong University

4. Xiamen University and Minjiang University

Publisher

ACM

Reference46 articles.

1. 2016. SIGCOMM to use Deep Learning for Paper Selection , An Email from SIGCOMM Mailing List on April 1. https://sigcomm.org/about/mailing-lists/. ( 2016 ). 2016. SIGCOMM to use Deep Learning for Paper Selection, An Email from SIGCOMM Mailing List on April 1. https://sigcomm.org/about/mailing-lists/. (2016).

2. 2018. Gurobi. https://www.gurobi.com. (2018). 2018. Gurobi. https://www.gurobi.com. (2018).

3. 2020. Open-source Prototype of NCFlow. https://github.com/netcontract/ncflow. (2020). 2020. Open-source Prototype of NCFlow. https://github.com/netcontract/ncflow. (2020).

4. 2021. Open-source Prototype of ARROW. https://github.com/hipersys-team/arrow. (2021). 2021. Open-source Prototype of ARROW. https://github.com/hipersys-team/arrow. (2021).

5. 2021. Open-source Prototype of Atomic Predicates Verifier. https://gitee.com/gdtongji/atomic_predicates_verifier. (2021). 2021. Open-source Prototype of Atomic Predicates Verifier. https://gitee.com/gdtongji/atomic_predicates_verifier. (2021).

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1. Toward Reproducing Network Research Results Using Large Language Models;Proceedings of the 22nd ACM Workshop on Hot Topics in Networks;2023-11-28

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