Align dataset card with VEFX-Bench v1.0

README.md

@@ -12,42 +12,93 @@ size_categories:
   - n<1K
 ---
 
-# VEFX-Bench: Video Editing Quality Benchmark
+# VEFX-Bench v1.0: Video Editing Quality Benchmark
+
+> **Frozen release:** VEFX-Bench v1.0 — frozen on 2026-08-03. The immutable data and evaluator identifiers are listed under [Reproducibility](#reproducibility).
 
 VEFX-Bench is a benchmark dataset for evaluating video editing model quality. It contains **300 original source videos** with editing instructions across **9 task categories**.
 
 ## Dataset Structure
 
 - `0000.mp4` through `0299.mp4`: 300 original source videos (720p)
-- `prompts.json`: Editing instructions indexed by video number
-- `benchmark_meta.json`: Metadata including category labels and filename mapping
+- `prompts.json`: editing instructions indexed by video number
+- `benchmark_meta.json`: the v1.0 manifest with category labels and filename mapping
 
 ## Usage
 
-1. Download all 300 videos and `prompts.json`
-2. Apply your video editing model following each prompt
-3. Save edited videos as `0000.mp4` through `0299.mp4` (matching index)
-4. Submit the zip to the [VEFX-Leaderboard](https://github.com/YOUR_ORG/VEFX-Leaderboard)
+1. Download the frozen v1.0 revision listed below.
+2. Apply your video editing model following each prompt.
+3. Save edited videos as `0000.mp4` through `0299.mp4` (matching index).
+4. Submit the zip to the [VEFX-Leaderboard](https://vefx-leaderboard.com/).
+
+Public evaluator reference code is available in [VEFX-Code](https://huggingface.co/spaces/VEFX-Reward/VEFX-Code/tree/main).
 
 ## Evaluation Dimensions
 
-- **IF (Instructional Following)**: How well the edit follows the instruction (1-4)
-- **RQ (Render Quality)**: Visual quality and temporal consistency (1-4)
-- **EE (Edit Exclusivity)**: Preservation of unrelated content (1-4)
+- **IF (Instructional Following):** how well the edit follows the instruction (1–4)
+- **RQ (Render Quality):** visual quality and temporal consistency (1–4)
+- **EE (Edit Exclusivity):** preservation of unrelated content (1–4)
+
+## Overall and Aggregation Order
+
+**Overall is the primary GeoAgg ranking metric; it is not the arithmetic average of IF, RQ, and EE.** For item \(j\), first normalize each soft dimension score to \([0,1]\):
+
+\[
+i_j=\frac{IF_j-1}{3},\qquad r_j=\frac{RQ_j-1}{3},\qquad e_j=\frac{EE_j-1}{3}.
+\]
+
+Then compute the item-level weighted geometric aggregate, with IF weighted twice:
+
+\[
+g_j=1+3\left(i_j^2r_je_j\right)^{1/4}.
+\]
+
+Finally, average the 300 item-level values:
+
+\[
+\mathrm{Overall}=\frac{1}{300}\sum_{j=1}^{300}g_j.
+\]
+
+Missing or failed items receive \(IF_j=RQ_j=EE_j=1\) before aggregation. This protocol is **mean of per-item GeoAgg**, not GeoAgg of the three dataset-level dimension means. The arithmetic mean of the three dimension averages may be shown separately as a diagnostic **Mean**, but it is not used for ranking.
 
 ## Task Categories
 
+These names and counts are taken directly from the frozen `benchmark_meta.json` manifest.
+
 | Category | Count |
-|----------|-------|
-| Style Transfer | varies |
-| Object Manipulation | varies |
-| Background Change | varies |
-| Color/Lighting | varies |
-| Motion/Animation | varies |
-| Text/Overlay | varies |
-| Composition | varies |
-| Removal/Inpainting | varies |
-| Complex/Multi-step | varies |
+|---|---:|
+| Attribute Editing | 33 |
+| Camera Angle Editing | 34 |
+| Camera Motion Editing | 33 |
+| Creative Edit | 33 |
+| Instance Editing | 33 |
+| Instance Motion Editing | 33 |
+| Quantity Editing | 34 |
+| Style Editing | 34 |
+| Visual Effect Editing | 33 |
+| **Total** | **300** |
+
+## Reproducibility
+
+| Artifact | Frozen identifier |
+|---|---|
+| Dataset revision | [`3bf997e7eb4fa0d0c2d56cce5ddfccc1dfbda235`](https://huggingface.co/datasets/xiangbog/VEFX-Bench/tree/3bf997e7eb4fa0d0c2d56cce5ddfccc1dfbda235) |
+| `benchmark_meta.json` SHA-256 | `277d89f5cf23af4163fe6ee120654210f51d19c6dee2d3aa76a3248471d1f333` |
+| Reward model revision | [`a15a8dbe1b3eb07ee0919e8de059f170436ec9ff`](https://huggingface.co/VEFX-Reward/VEFX-Reward-4B/tree/a15a8dbe1b3eb07ee0919e8de059f170436ec9ff) |
+| `model.safetensors` SHA-256 | `c3c0d03f770f0a73631206821922213de75413bb517f7d7a2fd9ab1f2c38f59d` |
+
+Download by immutable revision:
+
+```python
+from huggingface_hub import snapshot_download
+
+snapshot_download(
+    repo_id="xiangbog/VEFX-Bench",
+    repo_type="dataset",
+    revision="3bf997e7eb4fa0d0c2d56cce5ddfccc1dfbda235",
+    local_dir="./vefx_bench_v1",
+)
+```
 
 ## Citation