Datasets:
Tasks:
Graph Machine Learning
Modalities:
Text
Formats:
csv
Languages:
English
Size:
10K - 100K
ArXiv:
| task_categories: | |
| - graph-ml | |
| tags: | |
| - chemistry | |
| - molecular-design | |
| - in-context-learning | |
| - drug-discovery | |
| language: | |
| - en | |
| --- | |
| Paper: [Graph Diffusion Transformers are In-Context Molecular Designers](https://huggingface.co/papers/2510.08744) | |
| Code: https://github.com/liugangcode/DemoDiff | |
| --- | |
| # DemoDiff Downstream Context Data | |
| This dataset contains context data for the DemoDiff project, a diffusion-based molecular foundation model for in-context inverse molecular design. It provides contextual examples to guide molecular generation, enabling few-shot molecular design across diverse chemical tasks without task-specific fine-tuning. | |
| ## Structure | |
| Each task is organized as a separate folder in the repository root: | |
| ``` | |
| tasks/ | |
| ├── Albuterol_Similarity/ | |
| │ ├── positive.csv | |
| │ ├── medium.csv | |
| │ └── negative.csv | |
| ├── Amlodipine_MPO/ | |
| │ ├── positive.csv | |
| │ ├── medium.csv | |
| │ └── negative.csv | |
| └── ... (other tasks) | |
| ``` |