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..
Generative Graph Dictionary Learning
Authors: Zhichen Zeng, Ruike Zhu, Yinglong Xia, Hanqing Zeng, Hanghang Tong
ICML 2023 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Extensive experiments demonstrate the effectiveness of the obtained node and graph embeddings, and our algorithm achieves significant improvements over the state-of-the-art methods. and Extensive experiments show that FRAME achieves significant improvement on graph-level and node-level tasks, outperforming the state-of-the-art by 8.0% on graph classification, 0.5% on graph clustering, and 2.5% on node clustering, respectively. |
| Researcher Affiliation | Collaboration | 1Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, USA 2Meta, CA, USA. |
| Pseudocode | Yes | Algorithm 1 FRAME |
| Open Source Code | Yes | The code is implemented by authors from the University of Illinois and available at https://github.com/zhichenz98/FraMe-ICML23. |
| Open Datasets | Yes | All the real-world datasets we use are from (Morris et al., 2020) and available online1. 1https://chrsmrrs.github.io/datasets/ and lists datasets like "ENZYMES (Borgwardt et al., 2005)". |
| Dataset Splits | Yes | For graph classification, we apply 10-fold cross-validation on the benchmark datasets. |
| Hardware Specification | Yes | All experiments are conducted on the Linux platform with an Intel Xeon Gold 6240R CPU and an NVIDIA Tesla V100 SXM2 GPU. |
| Software Dependencies | No | The paper mentions specific software libraries used (POT toolbox, Gra Kel library, Karate Club library) but does not provide their version numbers. |
| Experiment Setup | No | The paper refers to hyperparameters (α, q, T, L) in Algorithm 1 and discusses the effect of σ in Section 4.4, but it does not provide specific numerical values for these or other training configurations (e.g., learning rate, batch size, optimizer settings) in the main text. |