| license: apache-2.0 | |
| # Dataset Details | |
| This dataset contains pretrained data constructed from academic text-rich graphs ([MAPLE](https://github.com/yuzhimanhua/MAPLE)) spanning three disciplines: Economics, Mathematics, and Geology. It is used for pretraining [RAMP](https://arxiv.org/abs/2603.14937) (Raw-text Anchored Message Passing), which recasts the LLM as a graph-native aggregation operator on text-rich graphs. | |
| The dataset includes the following files: | |
| - `pretrained_Economics.json` | |
| - `pretrained_Mathematics.json` | |
| - `pretrained_Geology.json` | |
| This is a release from our paper [LLM as Graph Kernel: Rethinking Message Passing on Text-Rich Graphs](https://arxiv.org/abs/2603.14937), so please cite it if using this dataset. | |
| # Citation | |
| ```bibtex | |
| @article{zhang2026llm, | |
| title={LLM as Graph Kernel: Rethinking Message Passing on Text-Rich Graphs}, | |
| author={Zhang, Ying and Yu, Hang and Zhang, Haipeng and Di, Peng}, | |
| journal={arXiv preprint arXiv:2603.14937}, | |
| year={2026} | |
| } | |
| ``` | |
| [](https://arxiv.org/abs/2603.14937) | |