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..
Dynamic Heterogeneous Graph Attention Neural Architecture Search
Authors: Zeyang Zhang, Ziwei Zhang, Xin Wang, Yijian Qin, Zhou Qin, Wenwu Zhu
AAAI 2023 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Extensive experiments on real-world dynamic heterogeneous graph datasets demonstrate that our proposed method significantly outperforms state-of-the-art baselines for tasks including link prediction, node classification and node regression. |
| Researcher Affiliation | Collaboration | Zeyang Zhang1*, Ziwei Zhang1, Xin Wang1 , Yijian Qin1, Zhou Qin2, Wenwu Zhu1 1Tsinghua University 2Alibaba Group |
| Pseudocode | No | The paper describes methods and algorithms textually but does not include a formally labeled pseudocode or algorithm block. |
| Open Source Code | Yes | The codes are publicly available1. 1https://github.com/wondergo2017/DHGAS |
| Open Datasets | Yes | We conduct experiments for the link prediction task on two datasets: an academic citation dataset Aminer (Ji et al. 2021) and a recommendation dataset Ecomm (Xue et al. 2020)... adopting two datasets: a business review dataset Yelp (Ji et al. 2021) and an e-commerce risk management dataset Drugs3. For the node regression task, we adopt an epidemic disease dataset COVID-19 (Fan et al. 2022). |
| Dataset Splits | No | The paper does not provide specific train/validation/test dataset split percentages or absolute counts for each split. |
| Hardware Specification | No | No specific hardware details (e.g., GPU/CPU models, processor types, memory amounts, or detailed computer specifications) used for running experiments are provided. |
| Software Dependencies | No | The paper does not provide specific software dependencies with version numbers (e.g., library or solver names with version numbers). |
| Experiment Setup | Yes | We report the results on the Aminer dataset when the localization constraint hyperparameters KLo is chosen from {4, 8, 10, 20, 40} |