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README.md

@@ -24,140 +24,6 @@ The ability to distinguish subtle differences between visually similar images is
 
 VLM-SubtleBench is a benchmark designed to evaluate VLMs on **subtle comparative reasoning** — detecting fine-grained differences between highly similar image pairs that are easy for humans but challenging for state-of-the-art VLMs. Unlike prior benchmarks restricted to natural image datasets, VLM-SubtleBench spans diverse domains including industrial, aerial, and medical imagery.
 
-## Key Findings
-
-- **Proprietary VLMs still struggle** with subtle visual comparison, leaving large gaps from human performance (best model: 77.8% vs. human: 95.5%).
-- **Simple prompting strategies** such as chain-of-thought, grid layouts, and overlapping images yield only limited improvements.
-- **VLMs are highly sensitive** to difficulty factors such as object size and count, with performance degrading sharply as scene complexity increases.
-- **Explicit reasoning helps**: models with stronger inherent reasoning capabilities achieve higher accuracy across all difference types.
-
-## Benchmark Summary
-
-| | |
-|---|---|
-| **Total QA pairs** | 12,923 |
-| **Difference types** | 10 |
-| **Image domains** | 6 (Natural, Industrial, Aerial, Synthetic, Medical) |
-| **Data sources** | 14 |
-| **Human captions** | 1,200 |
-| **Splits** | test (11,688) / val (1,235) |
-| **Task format** | Multiple-choice VQA + Image Difference Captioning |
-
-> **Note**: Medical domain images (MIMIC-CXR, 362 pairs) are not included due to licensing restrictions, but their QA entries are included in `qa.json`. See [Medical Data](#medical-data-mimic-cxr) below for instructions on how to obtain the images.
-
-## Difference Types
-
-VLM-SubtleBench covers 10 representative difference types, spanning from low-level visual variations to high-level semantic changes:
-
-| Category | Description | Count |
-|----------|-------------|-------|
-| Attribute | Variations in object properties (color, size, shape) | 1,196 |
-| State | Object condition changes (breakage, cracks, peeling) | 1,148 |
-| Emotion | Comparative judgments of facial expression intensity | 1,108 |
-| Temporal | Identifying which image depicts an earlier/later event | 1,117 |
-| Spatial | Changes in arrangement or relative position | 1,235 |
-| Existence | Whether an object has appeared or disappeared | 1,204 |
-| Quantity | Changes in object count | 1,599 |
-| Quality | Degradations such as blur, noise, or overexposure | 1,109 |
-| Viewpoint | Camera perspective changes (pan, tilt, roll, orbit) | 1,734 |
-| Action | Differences in human/object poses or activities | 1,111 |
-
-## Image Domains and Sources
-
-| Domain | Count | Sources |
-|--------|-------|---------|
-| Natural | 7,526 | CameraBench, ChangeIt, COCO, CREMA-D/RAVDESS/AFEW-VA/DAiSEE, MegaFruits, UCF-QNRF, VLM4D, YouTube-8M |
-| Synthetic | 3,190 | Procedurally generated primitive scenes (circles, squares, triangles on white backgrounds) |
-| Industrial | 1,202 | MVTec-AD, MVTec-LOCO |
-| Aerial | 643 | LEVIR-MCI, UBC |
-| Medical | 362* | MIMIC-CXR *(not included, see below)* |
-
-## Dataset Structure
-
-```
-VLM-SubtleBench/
-├── README.md
-├── qa.json                          # All QA pairs with metadata (including MIMIC)
-└── images/
-    ├── camerabench/                 # CameraBench — viewpoint
-    ├── changeit/                    # ChangeIt — state, quantity
-    │   ├── state/
-    │   └── quantity/
-    ├── coco/                        # COCO + Gemini edits — attribute, existence
-    │   ├── val2017/
-    │   ├── val2017_attribute_edit/
-    │   ├── val2017_existence_edit/
-    │   ├── train2017/
-    │   ├── train2017_attribute_edit/
-    │   └── train2017_existence_edit/
-    ├── emotion_videos/              # CREMA-D/RAVDESS/AFEW-VA/DAiSEE — emotion
-    ├── levir/                       # LEVIR-MCI — existence, quantity
-    │   ├── existence/
-    │   └── quantity/
-    ├── megafruits/                   # MegaFruits — quantity
-    ├── mvtec_ad/                    # MVTec-AD — attribute, state
-    ├── mvtec_loco/                  # MVTec-LOCO — quantity
-    ├── synthetic/                   # Synthetic primitives — attribute, existence, quantity, spatial, viewpoint
-    │   ├── attribute/
-    │   ├── existence/
-    │   ├── quantity/
-    │   ├── spatial/
-    │   └── viewpoint/
-    ├── ubc/                         # UBC — quantity
-    ├── ucf_qnrf/                    # UCF-QNRF — quantity
-    ├── vlm4d/                       # VLM4D — spatial, temporal
-    │   ├── spatial/
-    │   └── temporal/
-    └── yt8m/                        # YouTube-8M — action, quality, temporal
-        ├── action/
-        ├── quality/
-        └── temporal/
-```
-
-## QA Entry Format
-
-Each entry in `qa.json`:
-
-```json
-{
-  "image_1": "images/camerabench/processed_frames/1018.1.7/frame_1.png",
-  "image_2": "images/camerabench/processed_frames/1018.1.7/frame_2.png",
-  "question": "In which direction does the camera move from the first image to the second image?",
-  "answer": "backward",
-  "distractors": ["forward"],
-  "has_caption": false,
-  "caption": null,
-  "split": "test",
-  "metadata": {
-    "category": "viewpoint",
-    "domain": "natural",
-    "source": "camerabench",
-    "source_id": "0",
-    "raw_folder": "camera_pairs",
-    "generation_info": {
-      "movement_type": "dolly-out",
-      "original_labels": ["minimal-shaking", "complex-motion", "regular-speed", "dolly-out", "lead-tracking"],
-      "video_path": "videos_gif/1018.1.7.gif"
-    }
-  }
-}
-```
-
-| Field | Description |
-|-------|-------------|
-| `image_1`, `image_2` | Relative paths to the image pair |
-| `question` | The comparative question about the two images |
-| `answer` | Correct answer |
-| `distractors` | Incorrect answer choices |
-| `has_caption` | Whether a human-written difference caption is available |
-| `caption` | Human-written description of the difference between the images (null if unavailable) |
-| `split` | `test` or `val` |
-| `metadata.category` | One of the 10 difference types |
-| `metadata.domain` | Image domain (natural, industrial, aerial, synthetic, medical) |
-| `metadata.source` | Source dataset identifier |
-| `metadata.source_id` | Original ID within the source dataset |
-| `metadata.generation_info` | Source-specific metadata (varies by source, may be null) |
-
 ## Medical Data (MIMIC-CXR)
 
 The medical domain QA entries (362 attribute comparison pairs from MIMIC-CXR chest X-rays) are included in `qa.json`, but the corresponding images are not included due to [PhysioNet licensing requirements](https://physionet.org/content/mimic-cxr-jpg/2.1.0/).