README.md

metadata

dataset_info:
  features:
    - name: id
      dtype: string
    - name: domain
      dtype: string
    - name: task_type
      dtype: string
    - name: prompt
      dtype: string
    - name: image
      dtype: image
    - name: reference_frames
      sequence: image
    - name: reference_text
      sequence: string
    - name: protocol
      dtype: string
configs:
  - config_name: default
    data_files:
      - split: train
        path: dataset.parquet
license: mit
language:
  - en

Beyond the Last Frame: Process-aware Evaluation for Generative Video Reasoning

👀 About VIPER

• Overview: Process-aware evaluation for Generative Video Reasoning tasks.
• Statistics: 309 carefully curated samples spanning 6 distinct domains (i.e., temporal, structural, symbolic, spatial, physics and planning reasoning).
• 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.

Dataset Statistics

Domain Distribution

Domain	Total Samples	Task Types
Physics	32	experiment, game
Planning	44	navigation, obj_manipulation
Spatial	60	block_rotate, dice, image_restore
Structural	70	chess, maze, sudoku, ttt
Symbolic	60	knowledge, math, multimodal
Temporal	43	obj_move, zoom

📦 Dataset Usage

Download

from datasets import load_dataset

# Load the full dataset
dataset = load_dataset("Monosail/VIPER")

Data Fields

• id: Unique identifier for the sample
• domain: The reasoning domain (Physics, Planning, Spatial, Structural, Symbolic, Temporal)
• task_type: Specific task category within the domain
• prompt: Text prompt describing the task
• image: The input image
• reference_frames: Ground-truth image frames
• reference_texts: Ground-truth text descriptions
• protocol: Process-level task constraints

📝 Citation

If you find our benchmark useful, please consider citing us:

@article{li2026viper,
  title={Beyond the Last Frame: Process-aware Evaluation for Generative Video Reasoning},
  author={Li, Yifan and Gu, Yukai and Min, Yingqian and Liu, Zikang and Du, Yifan and Zhou, Kun and Yang, Min and Zhao, Wayne Xin and Qiu, Minghui},
  journal={arXiv preprint arXiv:2512.24952},
  year={2025}
}