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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  license: mit
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  language:
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  - en
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- size_categories:
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- - n<1K
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  ---
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- # VIPER Benchmark
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- ## Dataset Description
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- VIPER (VIdeo Process Evaluation for Reasoning tasks) is a comprehensive benchmark for Generative Video Reasoning (GVR) tasks.
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- ### Dataset Summary
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-
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- This dataset contains **309 samples** spanning **6 distinct reasoning domains**:
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-
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- - **Physics**: Understanding of physical laws and dynamics (32 samples)
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- - **Planning**: Spatial navigation and object manipulation (44 samples)
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- - **Spatial**: 3D spatial reasoning and transformations (60 samples)
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- - **Structural**: Pattern recognition and constraint satisfaction (70 samples)
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- - **Symbolic**: Knowledge reasoning and mathematical problem-solving (60 samples)
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- - **Temporal**: Temporal dynamics and object tracking (43 samples)
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-
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- ## Dataset Structure
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-
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- ### Data Instances
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-
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- Each instance contains:
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-
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- ```json
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- {
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- "domain": "Spatial",
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- "id": "block_rotate_0",
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- "image": "Spatial/images/block_rotate_0.jpg",
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- "reference": {
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- "frames": ["Spatial/references/block_rotate_0_0.jpg"],
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- "text": []
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- },
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- "prompt": "A structure composed of 9 cubes viewed from...",
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- "protocol": ["Maintain the block structure..."],
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- "task_type": "block_rotate"
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- }
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- ```
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-
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- ### Data Fields
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-
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- - `domain`: The reasoning domain (Physics, Planning, Spatial, Structural, Symbolic, Temporal)
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- - `id`: Unique identifier for the sample
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- - `image`: Path to the input image
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- - `reference`: Reference materials for evaluation
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- - `frames`: Reference image frames
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- - `text`: Reference text descriptions
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- - `prompt`: Text prompt describing the task or desired output
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- - `protocol`: Evaluation criteria or constraints
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- - `task_type`: Specific task category within the domain
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  ## Dataset Statistics
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  | Symbolic | 60 | knowledge, math, multimodal |
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  | Temporal | 43 | obj_move, zoom |
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- ### Task Distribution by Domain
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-
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- **Physics** (32 samples):
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- - experiment: 18 samples
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- - game: 14 samples
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- **Planning** (44 samples):
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- - navigation: 25 samples
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- - obj_manipulation: 19 samples
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-
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- **Spatial** (60 samples):
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- - block_rotate: 25 samples
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- - dice: 20 samples
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- - image_restore: 15 samples
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-
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- **Structural** (70 samples):
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- - chess: 20 samples
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- - maze: 20 samples
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- - sudoku: 20 samples
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- - ttt: 10 samples
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-
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- **Symbolic** (60 samples):
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- - knowledge: 20 samples
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- - math: 20 samples
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- - multimodal: 20 samples
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-
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- **Temporal** (43 samples):
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- - obj_move: 25 samples
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- - zoom: 18 samples
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-
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- ## Usage
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  ```python
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  from datasets import load_dataset
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  ```
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- ## Citation Information
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ```bibtex
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  @article{li2026viper,
 
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  ---
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+ dataset_info:
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+ features:
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+ - name: id
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+ dtype: string
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+ - name: domain
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+ dtype: string
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+ - name: task_type
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+ dtype: string
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+ - name: prompt
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+ dtype: string
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+ - name: image
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+ dtype: image
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+ - name: reference_frames
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+ sequence: image
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+ - name: reference_text
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+ sequence: string
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+ - name: protocol
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+ dtype: string
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+ configs:
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+ - config_name: default
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+ data_files:
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+ - split: train
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+ path: dataset.parquet
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  license: mit
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  language:
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  - en
 
 
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  ---
 
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+ # Beyond the Last Frame: Process-aware Evaluation for Generative Video Reasoning
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+ ## 👀 About VIPER
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+ - Overview: Process-aware evaluation for Generative Video Reasoning tasks.
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+ - Statistics: 309 carefully curated samples spanning 6 distinct domains (i.e., temporal, structural, symbolic, spatial, physics and planning reasoning).
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+ - New Metric: Process-outcome Consistency (POC@$r$). POC@$r$ evaluate video correctness at both process- and outcome-level, with multiple frames uniformly sampled from the whole video at rate $r$, instead of the last frame only.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ## Dataset Statistics
 
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  | Symbolic | 60 | knowledge, math, multimodal |
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  | Temporal | 43 | obj_move, zoom |
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+ ## 📦 Dataset Usage
 
 
 
 
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+ ### Download
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ```python
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  from datasets import load_dataset
 
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  ```
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+ ### Data Fields
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+
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+ - `id`: Unique identifier for the sample
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+ - `domain`: The reasoning domain (Physics, Planning, Spatial, Structural, Symbolic, Temporal)
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+ - `task_type`: Specific task category within the domain
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+ - `prompt`: Text prompt describing the task
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+ - `image`: The input image
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+ - `reference_frames`: Ground-truth image frames
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+ - `reference_texts`: Ground-truth text descriptions
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+ - `protocol`: Process-level task constraints
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+
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+
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+
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+ ## 📝 Citation
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+
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+ If you find our benchmark useful, please consider citing us:
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  ```bibtex
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  @article{li2026viper,