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Implementation:Open compass VLMEvalKit WorldSense

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Revision as of 13:33, 16 February 2026 by Admin (talk | contribs) (Auto-imported from implementations/Open_compass_VLMEvalKit_WorldSense.md)
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Field Value
source VLMEvalKit
domain Vision, Benchmarking, Video World Understanding

Overview

Benchmark dataset implementation for WorldSense video world understanding evaluation in VLMEvalKit.

Description

WorldSense inherits from VideoBaseDataset and implements the WorldSense benchmark for evaluating video-based world understanding through multiple-choice questions. The TYPE field is set to 'Video-MCQ'. It supports multiple input modalities including frames without subtitles, frames with subtitles, and frames with audio, each with dedicated prompt templates guiding the model to respond with option letters (A, B, C, or D).

Usage

Registered in vlmeval/dataset/__init__.py and invoked through build_dataset() by benchmark name.

Code Reference

  • Source: vlmeval/dataset/worldsense.py, Lines: L1-336
  • Import: from vlmeval.dataset.worldsense import WorldSense

Signature:

class WorldSense(VideoBaseDataset):
    TYPE = 'Video-MCQ'
    MD5 = 'bfc25490be4080aa5494b883370b6b1f'
    ...

I/O Contract

Direction Description
Inputs TSV dataset file with video paths and world understanding MCQ questions
Outputs Evaluation results DataFrame with MCQ accuracy scores

Usage Examples

from vlmeval.dataset import build_dataset
dataset = build_dataset('WorldSense')

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Principle
Implementation
Heuristic
Environment