Add model card and metadata

README.md

@@ -1,3 +1,30 @@
 ---
 license: apache-2.0
+pipeline_tag: image-to-image
 ---
+
+# Linear Recurrent Unit with Semantic Modulation for Image Super-Resolution
+
+This repository contains the pre-trained weights for LSM, presented in the paper [Linear Recurrent Unit with Semantic Modulation for Image Super-Resolution](https://huggingface.co/papers/2606.19901).
+
+- **GitHub Repository:** [https://github.com/MingyuChoi-run/LSM](https://github.com/MingyuChoi-run/LSM)
+- **Paper:** [https://arxiv.org/abs/2606.19901](https://arxiv.org/abs/2606.19901)
+
+## Abstract
+Linear recurrent unit (LRU), designed with a principled formulation for stable linear recurrence, has demonstrated promising accuracy and robustness on long-range dependency tasks. However, its static parameterization and single-scan method limits its applicability to 2D vision tasks. In this study, we propose a LRU-based restoration network with a semantic modulating unit (SMU) to achieve a harmonious balance between performance and efficiency in single-image super-resolution. The SMU plays three key roles: LRU modulation, spatial categorization, and feature enhancement through learned prototype.
+
+## Citation
+
+```bibtex
+@InProceedings{Choi_2026_CVPR,
+    author    = {Choi, Mingyu and Han, Woo Kyoung and Im, Sunghoon and Jin, Kyong Hwan},
+    title     = {Linear Recurrent Unit with Semantic Modulation for Image Super-Resolution},
+    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Findings},
+    month     = {June},
+    year      = {2026},
+    pages     = {4950-4960}
+}
+```
+
+## Acknowledgements
+This code is built on [BasicSR](https://github.com/XPixelGroup/BasicSR).