Multiplex Graph Representation Learning via Bi-level Optimization
Authors: Yudi Huang, Yujie Mo, Yujing Liu, Ci Nie, Guoqiu Wen, Xiaofeng Zhu
IJCAI 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Extensive experiments show that our model achieves the superior performance on node classification tasks on all datasets. |
| Researcher Affiliation | Academia | 1School of Computer Science and Engineering, Guangxi Normal University, Guilin 541004, China 2Guangxi Key Lab of Multisource Information Mining Security, Guilin 541004, China 3School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described in this paper. |
| Open Datasets | Yes | The used datasets include 2 citation multiplex graph datasets, i.e., ACM [Jin et al., 2021] and DBLP [Jin et al., 2021], and two movie multiplex graph datasets, i.e., IMDB [Jin et al., 2021] and Freebase [Mo et al., 2023a]. |
| Dataset Splits | No | The paper mentions using node classification tasks and datasets but does not provide specific train/validation/test dataset split information (exact percentages, sample counts, citations to predefined splits, or detailed splitting methodology) for their experiments. |
| Hardware Specification | No | The paper does not provide specific hardware details used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details (e.g., library or solver names with version numbers) needed to replicate the experiment. |
| Experiment Setup | No | The paper does not contain specific experimental setup details such as concrete hyperparameter values, training configurations, or system-level settings in the main text. |