Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
On Generalized Degree Fairness in Graph Neural Networks
Authors: Zemin Liu, Trung-Kien Nguyen, Yuan Fang
AAAI 2023 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Extensive experiments on three benchmark datasets demonstrate the effectiveness of our model on both accuracy and fairness metrics. |
| Researcher Affiliation | Academia | 1 National University of Singapore, Singapore 2 Singapore Management University, Singapore |
| Pseudocode | No | The paper describes its methods using equations and prose, but does not include a formal pseudocode or algorithm block. |
| Open Source Code | No | The paper does not provide any statement or link indicating the availability of open-source code for the methodology described. |
| Open Datasets | Yes | We use two Wikipedia networks, Chameleon and Squirrel (Pei et al. 2020)... We also use a citation network EMNLP (Ma et al. 2021)... |
| Dataset Splits | Yes | For all the datasets, we randomly split the nodes into training, validation and test set with proportion 6:2:2. |
| Hardware Specification | No | The paper does not provide specific details about the hardware (e.g., CPU, GPU models) used for running the experiments. |
| Software Dependencies | No | The paper discusses different GNN backbones but does not list specific software dependencies (e.g., Python, PyTorch, TensorFlow) with version numbers. |
| Experiment Setup | No | The paper states 'For other hyper-parameter settings, please refer to Appendix E.', indicating that specific details are not present in the main text. |