Update README.md

README.md

@@ -21,6 +21,99 @@ configs:
     path: "bench/*.json"
 ---
 
-In each json, there are three keys: `action_prompt`, `input`, and `output`, where `input` and `output` are the structure information in CIF format. Insert `action_prompt` and `input` into the system prompt and then call LLM/Agent to start the task.
+# AtomWorldBench
 
-The `bench_data` folder contains the data used in the AtomWorld Bench. Besides, we have generated ~5K data for each action, which can be used as training set.
+AtomWorldBench is a benchmark and dataset for evaluating the ability of Large Language Models (LLMs) and agents to perform **3D crystal structure manipulation** from natural language instructions.
+
+Given an input crystal structure in CIF format and a textual instruction, the model must generate the resulting crystal structure after applying the requested modification.
+
+The dataset is released alongside the AtomWorld benchmark framework and is intended for:
+
+- Benchmarking spatial reasoning abilities of LLMs
+- Training structure-editing agents
+- Supervised fine-tuning (SFT)
+- Reinforcement learning and reward modeling research
+- Materials-science agent evaluation
+
+## Task Description
+
+Each example contains:
+
+```json
+{
+  "action_prompt": "...",
+  "input": "...",
+  "output": "...",
+  // ... other metadata
+}
+```
+
+In addition, the repository provides a shared `system_prompt.txt` that can be used for every task.
+
+where:
+
+| Field | Description |
+|---------|-------------|
+| `action_prompt` | Natural-language instruction describing the required structure modification |
+| `input` | Input crystal structure in CIF format |
+| `output` | Ground-truth crystal structure after applying the instruction |
+
+The task is:
+
+> Given (`action_prompt`, `input`), generate `output`.
+
+
+The `bench_data` folder contains the data used in the AtomWorld Bench. Besides, we have generated ~5K data for each action, which can be used as training set.
+
+
+## Evaluation
+
+AtomWorld uses structure-aware evaluation rather than text matching.
+
+Typical verification steps include:
+
+1. CIF parsing
+2. Atom-count verification
+3. Structure matching
+4. RMSD calculation
+
+For official evaluation and benchmarking tools, see the AtomWorld repository:
+
+https://github.com/MasterAI-EAM/atomworld
+
+## Repository Relationship
+
+This Hugging Face repository contains the released datasets only.
+
+The GitHub repository provides:
+
+- evaluation code
+- benchmark runner
+- dataset generation pipeline
+- API server for agent benchmarking
+- visualization and analysis utilities
+
+## Limitations
+
+The dataset focuses on crystal-structure manipulation and does not directly evaluate:
+
+- materials-property prediction
+- electronic structure reasoning
+- synthesis planning
+- reaction prediction
+
+Performance on AtomWorldBench should therefore be interpreted as a measure of structure-editing and spatial reasoning ability rather than general materials-science expertise.
+
+## Citation
+
+If you use AtomWorldBench in your work, please cite:
+
+```bibtex
+@misc{lv2025atomworldbenchmarkevaluatingspatial,
+      title={AtomWorld: A Benchmark for Evaluating Spatial Reasoning in Large Language Models on Crystalline Materials},
+      author={Taoyuze Lv and Alexander Chen and Fengyu Xie and Chu Wu and Jeffrey Meng and Dongzhan Zhou and Bram Hoex and Zhicheng Zhong and Tong Xie},
+      year={2025},
+      eprint={2510.04704},
+      archivePrefix={arXiv},
+      primaryClass={cond-mat.mtrl-sci}
+}