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diff --git a/README.md b/README.md
index e5f99753cd5578d5f86c70bb7da94c52f8fe692b..5b3dae2116cf7bfad0e4d0b0e3f86d8bdb5e5ea7 100644
--- a/README.md
+++ b/README.md
@@ -1,3 +1,82 @@
 ---
 license: cc-by-nc-4.0
+language:
+- en
+task_categories:
+- image-to-image
+tags:
+- super-resolution
+- scene-text
+- text-aware-super-resolution
+- reasoning
+- benchmark
+pretty_name: ReasonText
+size_categories:
+- n<1K
 ---
+
+# ReasonText
+
+**ReasonText** is a benchmark for **reasoning-required text-aware image super-resolution (TAISR)**, from the paper
+*"Reading the Unreadable: Text-Aware Image Super-Resolution Needs Reasoning"* (NeurIPS 2026). Some degraded text
+cannot be read from local pixels alone; humans read it by reasoning over context, prior knowledge, or logic.
+ReasonText makes this measurable with human-annotated word-level text and a per-instance **difficulty level**.
+
+- 📄 Paper: `<paper link — fill in>`
+- 💻 Code (metric **GTTCA** + method **RTC**, full usage): `<GitHub link — fill in>`
+- 🖼️ Model SR outputs (for reproduction): [Jasonleex1995/ReasonText-SR-outputs](https://huggingface.co/datasets/Jasonleex1995/ReasonText-SR-outputs)
+
+## Contents
+
+```
+HR/                     # 513 high-resolution images (512×512 PNG)
+LR/                     # 513 low-resolution images (128×128 PNG, ×4)
+ReasonText-meta.json    # word-level annotations, keyed by image stem
+```
+
+`ReasonText-meta.json` maps each image stem (e.g. `DRealSR__Canon_10__256_01`) to:
+
+```jsonc
+{
+  "hr_image": "HR/<stem>.png",
+  "lr_image": "LR/<stem>.png",
+  "annotations": [
+    {
+      "hr_coords":       [[x1,y1], ...],   // word-level polygon in HR pixel coordinates
+      "text":            "BEST",           // ground-truth transcription
+      "text_rotation":   0,                // 0 / 90 / 180 / 270 (counter-clockwise)
+      "text_flipped":    false,
+      "text_difficulty": "Level 1",        // Level 1 / Level 2 / Level 3
+      "reason_types":    ["Context","Prior"] // Level 2 only: subset of Prior / Context / Logic
+    }
+  ]
+}
+```
+
+## Difficulty levels
+
+Assigned by 10 annotators in two phases (cropped text region, then full LR image):
+
+| Level | Meaning | Instances |
+|---|---|---|
+| **Level 1** | locally recoverable (readable from the text region alone) | 1,754 |
+| **Level 2** | **reasoning-required** (not L1, but recoverable using context / prior knowledge / logic) | 709 |
+| **Level 3** | unrecoverable even from the full LR image | 1,522 |
+
+**513 images / 3,985 annotations** in total. This is the paper's evaluation set (LR–HR pairs containing *only*
+Level 3 instances are excluded). Level 2 is the focus of the paper; its `reason_types` mark the decisive cue
+(**Prior** knowledge, image **Context**, or **Logic**) and should be treated as a set.
+
+## Provenance & license
+
+ReasonText images are drawn from **RealSR (v3)** [Cai et al., ICCV 2019] and **DRealSR** [Wei et al., ECCV 2020];
+the difficulty/text annotations are our contribution. Released under **CC BY-NC 4.0 (non-commercial research use
+only)**. Please cite our paper together with RealSR-v3 and DRealSR, and refer to those datasets for their terms.
+
+## Citation
+
+```bibtex
+<bibtex — fill in>
+```
+
+RealSR-v3 [Cai et al., ICCV 2019] and DRealSR [Wei et al., ECCV 2020] — please cite both.
diff --git a/ReasonText-meta.json b/ReasonText-meta.json
new file mode 100644
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--- /dev/null
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