Datasets:
Tasks:
Graph Machine Learning
Modalities:
Text
Formats:
csv
Languages:
English
Size:
10K - 100K
ArXiv:
metadata
task_categories:
- graph-ml
tags:
- chemistry
- molecular-design
- in-context-learning
- drug-discovery
language:
- en
Paper: Graph Diffusion Transformers are In-Context Molecular Designers 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)