Add dataset card for LLEMABench

README.md

@@ -0,0 +1,55 @@
+---
+license: mit
+task_categories:
+- other
+tags:
+- materials-science
+- chemistry
+- ai-for-science
+---
+
+# LLEMABench
+
+LLEMABench is a benchmark suite for materials discovery tasks, introduced in the paper [LLEMA: Evolutionary Search with LLMs for Multi-Objective Materials Discovery](https://huggingface.co/papers/2510.22503). 
+
+The benchmark consists of 14 realistic tasks across various domains, including:
+- Electronics
+- Energy
+- Coatings
+- Optics
+- Aerospace
+
+It evaluates candidates based on chemical plausibility, thermodynamic stability, and multi-objective property alignment (e.g., bandgap, formation energy, and bulk modulus).
+
+## Links
+
+- **GitHub Repository**: [https://github.com/scientific-discovery/LLEMA](https://github.com/scientific-discovery/LLEMA)
+- **Paper**: [https://huggingface.co/papers/2510.22503](https://huggingface.co/papers/2510.22503)
+
+## Evaluation and Usage
+
+The official implementation provides scripts to evaluate CIF files for validity (property constraints) and thermodynamic stability.
+
+### Validity Analysis
+To evaluate CIF files against task-specific property constraints:
+```bash
+python calculate_validity.py --tasks "Hard, Stiff Ceramics"
+```
+
+### Stability Analysis
+To analyze the thermodynamic stability of candidates from validity analysis results:
+```bash
+python calculate_stability.py --task <task_name>
+```
+
+## Citation
+
+```bibtex
+@inproceedings{abhyankar2026llema,
+        title={LLEMA: Accelerating Materials Design via {LLM}-Guided Evolutionary Search},
+        author={Abhyankar, Nikhil and Kabra, Sanchit and Desai, Saaketh and Reddy, Chandan K},
+        booktitle={The Fourteenth International Conference on Learning Representations (ICLR)},
+        year={2026},
+        url={https://openreview.net/forum?id=TIqzhBvCNB}
+}
+```