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README.md

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+---
+license: mit
+task_categories:
+- text-generation
+language:
+- en
+tags:
+- molecules
+- chemistry
+- pretraining
+- graph-llm
+- smiles
+pretty_name: DQFormer Encoder Pretraining Data
+size_categories:
+- 10M<n<100M
+---
+
+# DQFormer Encoder Pretraining Data
+
+Pretraining corpus for the **EDT-Former** Stage 1 encoder (DQ-Former), as described in the ICLR 2026 paper:
+
+> **Entropy-Guided Dynamic Tokens for Graph-LLM Alignment in Molecular Understanding**
+> Zihao Jing, Qiuhao Zeng, Ruiyi Fang, Yan Sun, Boyu Wang, Pingzhao Hu
+> *ICLR 2026* · [Paper](https://www.arxiv.org/abs/2602.02742) · [Code](https://github.com/selmiss/DQ-Former)
+
+## Dataset Description
+
+This dataset is used to train the Stage 1 DQ-Former encoder, which learns to align molecular graph representations with text. It is derived from PubChem molecules annotated with BRICS fragment IDs and entropy-guided graph IDs.
+
+## Data Format
+
+Each split is stored as a JSONL file where each line is a JSON object representing one molecule-text pair, including graph features, SMILES, and associated text descriptions.
+
+| Split | File | Size |
+|-------|------|------|
+| Train | `train.jsonl` | ~12 GB |
+| Validation | `val.jsonl` | ~37 MB |
+| Test | `test.jsonl` | ~78 MB |
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("zihaojing/DQFormer-pretrain-data")
+```
+
+Or point to it in the EDT-Former config:
+
+```yaml
+# configs/stage1_dqw2d/data_config_preprocessed.yaml
+use_preprocessed: true
+preprocessed_data: zihaojing/DQFormer-pretrain-data
+```
+
+## Related Resources
+
+| Resource | Link |
+|----------|------|
+| SFT Data | [zihaojing/DQFormer-sft-data](https://huggingface.co/datasets/zihaojing/DQFormer-sft-data) |
+| Encoder (Stage 1) | [zihaojing/DQFormer-encoder](https://huggingface.co/zihaojing/DQFormer-encoder) |
+| Full Model (Stage 2) | [zihaojing/DQFormer-model](https://huggingface.co/zihaojing/DQFormer-model) |
+| Code | [selmiss/DQ-Former](https://github.com/selmiss/DQ-Former) |
+
+## Citation
+
+```bibtex
+@inproceedings{jing2026edtformer,
+  title={Entropy-Guided Dynamic Tokens for Graph-LLM Alignment in Molecular Understanding},
+  author={Jing, Zihao and Zeng, Qiuhao and Fang, Ruiyi and Sun, Yan and Wang, Boyu and Hu, Pingzhao},
+  booktitle={International Conference on Learning Representations (ICLR)},
+  year={2026}
+}
+```