Add model card with paper, code, and project links

README.md

@@ -1,3 +1,56 @@
----
-license: mit
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+---
+license: mit
+pipeline_tag: other
+---
+
+# PRISM: Position-encoded Regressive Inverse Spectral Model
+
+PRISM is a unified decoder-only autoregressive transformer designed for **inverse thin-film optical design**. Given a target optical spectrum, it generates a multilayer thin-film stack (specifying materials and thicknesses) whose physical response matches the target.
+
+- **Paper:** [PRISM: Position-encoded Regressive Inverse Spectral Model for Multilayer Thin-Film Design](https://huggingface.co/papers/2605.26502)
+- **Project Page:** [PRISM Playground](https://www.prism-playground.com/)
+- **Code:** [GitHub Repository](https://github.com/wang-henry4/prism)
+
+## Architecture Key Innovations
+
+PRISM introduces three primary architectural ideas that distinguish it from prior sequence-to-sequence approaches:
+
+1.  **Spectrum prefix conditioning**: The target spectrum is projected into a single learned token and prepended to the decoder sequence, utilizing causal self-attention for target injection.
+2.  **Cumulative-depth RoPE**: Instead of standard sequential token indices, Rotary Position Embeddings (RoPE) use the running cumulative physical depth (in nm) of the film stack. This provides the attention mechanism with a physically meaningful distance metric related to optical path length.
+3.  **Dual output heads**: A shared transformer backbone feeds two specialized heads:
+    - **Material Head**: Predicts discrete material selection.
+    - **Thickness Head**: A multi-layer MLP that treats thickness as a continuous regression target (nm), predicting a thickness for *every* material in the vocabulary at each position to enable joint beam search.
+
+## Getting Started
+
+### Installation
+
+```bash
+git clone https://github.com/wang-henry4/prism
+cd prism
+pip install -e .
+```
+
+### Evaluation
+
+You can evaluate a checkpoint using the provided script. It decodes structures, re-simulates them via the Transfer Matrix Method (TMM), and compares them against target spectra.
+
+```bash
+python evaluate.py \
+    --checkpoint saved_models/inverse/inverse_v1/best.pt \
+    --val_path ./data/val/part_000.arrow \
+    --nk_dir ./nk --n_samples 1000 \
+    --beam_width 5 --length_penalty 0.3 \
+    --plot_dir ./plots/inverse_eval
+```
+
+## Citation
+
+```bibtex
+@article{wang2026prism,
+  title={PRISM: Position-encoded Regressive Inverse Spectral Model for Multilayer Thin-Film Design},
+  author={Wang, Runtian and Xue, Renhao and Chen, Baige and Wu, Hao},
+  journal={arXiv preprint arXiv:2605.26502},
+  year={2026}
+}
+```