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README.md

@@ -1,44 +1,71 @@
----
-dataset_info:
-  features:
-    - name: id
-      dtype: string
-    - name: turncase
-      dtype: string
-    - name: num_turns
-      dtype: int32
-    - name: prompt_category
-      dtype: string
-    - name: eval_focus
-      dtype: string
-    - name: prompt
-      dtype: string
-    - name: golden_answer
-      dtype: string
-    - name: image
-      dtype: image
-    - name: images
-      sequence:
-        dtype: image
-    - name: num_images
-      dtype: int32
-    - name: tool_trajectory
-      dtype: string
-    - name: rubrics
-      dtype: string
-  splits:
-    - name: train
-      num_bytes: 5981789093
-      num_examples: 1204
-  download_size: 5981789093
-  dataset_size: 5981789093
-  configs:
-    - config_name: default
-      data_files:
-        - split: train
-          path: data/*.parquet
----
-
-VisuAlToolBench is a challenging benchmark to assess tool-enabled visual perception, transformation, and reasoning in multimodal LLMs. It evaluates whether models can not only think about images but also think with images by actively manipulating visuals (e.g., crop, edit, enhance) and integrating general-purpose tools to solve complex tasks. The dataset contains single-turn and multi-turn tasks across diverse domains, each accompanied by detailed rubrics for systematic evaluation. Parquet files under `data/` are auto-indexed by the Hub and power the Dataset Viewer.
-
-Paper: [BEYOND SEEING: Evaluating Multimodal LLMs on Tool-enabled Image Perception, Transformation, and Reasoning](https://arxiv.org/pdf/2510.12712)
+# VisToolBench Dataset
+
+A benchmark dataset for evaluating vision-language models on tool-use tasks.
+
+## Dataset Statistics
+
+- **Total samples**: 1204
+- **Single-turn**: 603
+- **Multi-turn**: 601
+
+## Schema
+
+| Column | Type | Description |
+|--------|------|-------------|
+| `id` | string | Unique task identifier |
+| `turncase` | string | Either "single-turn" or "multi-turn" |
+| `num_turns` | int | Number of conversation turns (1 for single-turn) |
+| `prompt_category` | string | Task category (e.g., "medical", "scientific", "general") |
+| `eval_focus` | string | What aspect is being evaluated (e.g., "visual_reasoning", "tool_use") |
+| `image` | Image | Preview image (so HF viewer always shows an image) |
+| `turn_prompts` | List[string] | Per-turn prompts (single-turn → list of length 1) |
+| `turn_images` | List[Image] | Per-turn images (single-turn → list of length 1) |
+| `turn_golden_answers` | List[string] | Per-turn golden answers |
+| `turn_tool_trajectories` | List[string] | Per-turn tool trajectories (JSON strings) |
+| `rubrics_by_turn` | List[string] | Per-turn rubric dicts as JSON strings (includes weights + metadata) |
+| `num_images` | int | Number of turn images (usually equals `num_turns`) |
+| `images` | List[Image] | Alias of `turn_images` for HF viewer friendliness |
+| `rubrics` | string | Convenience JSON string keyed by turn (keys like `turn_1`, `turn_2`, ...) |
+
+## Rubrics Format
+
+Each rubric entry contains:
+- `description`: What the rubric evaluates
+- `weight`: Importance weight (1-5)
+- `objective/subjective`: Whether evaluation is objective or subjective
+- `explicit/implicit`: Whether the answer is explicit or implicit in the image
+- `category`: List of categories (e.g., "instruction following", "truthfulness")
+- `critical`: Whether this is a critical rubric ("yes"/"no")
+- `final_answer`: Whether this relates to the final answer ("yes"/"no")
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+# Load the dataset
+ds = load_dataset("path/to/dataset")
+
+# Access a sample
+sample = ds['test'][0]
+print(sample['turn_prompts'])       # list[str]
+print(sample['turn_images'][0])     # PIL Image (turn 1)
+
+# Parse rubrics for turn 1
+import json
+turn1_rubrics = json.loads(sample['rubrics_by_turn'][0])
+for rubric_id, rubric in turn1_rubrics.items():
+    print(f"{rubric['description']} (weight: {rubric['weight']})")
+```
+
+## Splits
+
+- `test`: Full dataset (1204 samples)
+
+## License
+
+[Specify license here]
+
+## Citation
+
+[Add citation here]

manifest.json

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+{
+  "single_json": "single_turn_data_corrected_with_rubrics_weights.json",
+  "multi_json": "multi_turn_data_corrected_with_rubrics_weights.json",
+  "counts": {
+    "single": 603,
+    "multi": 601,
+    "total": 1204
+  },
+  "columns": [
+    "id",
+    "turncase",
+    "num_turns",
+    "prompt_category",
+    "eval_focus",
+    "image",
+    "turn_prompts",
+    "turn_images",
+    "turn_golden_answers",
+    "turn_tool_trajectories",
+    "rubrics_by_turn",
+    "images",
+    "rubrics",
+    "num_images"
+  ],
+  "out_parquet": "hf_upload_final_corrected_v2/test.parquet"
+}

test.parquet

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+version https://git-lfs.github.com/spec/v1
+oid sha256:522cbe9b0ac1b99fcebd98821a0d234526078e2cc0e42c2378c5a862422f1255
+size 10249225530