A-OKVQA#

Overview#

A-OKVQA (Augmented OK-VQA) is a benchmark designed to evaluate commonsense reasoning and external world knowledge in visual question answering. It extends beyond basic VQA tasks that rely solely on image content, requiring models to leverage a broad spectrum of commonsense and factual knowledge about the world.

Task Description#

Task Type: Visual Question Answering with Knowledge Reasoning
Input: Image + natural language question requiring external knowledge
Output: Answer (multiple-choice or open-ended)
Domains: Commonsense reasoning, factual knowledge, visual understanding

Key Features#

Requires commonsense reasoning beyond direct visual observation
Combines visual understanding with external world knowledge
Includes both multiple-choice and open-ended question formats
Questions annotated with rationales explaining the reasoning process
More challenging than standard VQA benchmarks

Evaluation Notes#

Default evaluation uses the validation split
Primary metric: Accuracy for multiple-choice questions
Uses Chain-of-Thought (CoT) prompting for better reasoning
Questions require reasoning beyond what is directly visible in images

Properties#

Property	Value
Benchmark Name	`a_okvqa`
Dataset ID	HuggingFaceM4/A-OKVQA
Paper	N/A
Tags	`Knowledge`, `MCQ`, `MultiModal`
Metrics	`acc`
Default Shots	0-shot
Evaluation Split	`validation`

Data Statistics#

Metric	Value
Total Samples	1,145
Prompt Length (Mean)	310.84 chars
Prompt Length (Min/Max)	276 / 405 chars

Image Statistics:

Metric	Value
Total Images	1,145
Images per Sample	min: 1, max: 1, mean: 1
Resolution Range	305x229 - 640x640
Formats	jpeg

Sample Example#

Subset: default

{
  "input": [
    {
      "id": "3d2b0351",
      "content": [
        {
          "text": "Answer the following multiple choice question. The last line of your response should be of the following format: 'ANSWER: [LETTER]' (without quotes) where [LETTER] is one of A,B,C,D. Think step by step before answering.\n\nWhat is in the motorcyclist's mouth?\n\nA) toothpick\nB) food\nC) popsicle stick\nD) cigarette"
        },
        {
          "image": "[BASE64_IMAGE: jpeg, ~53.4KB]"
        }
      ]
    }
  ],
  "choices": [
    "toothpick",
    "food",
    "popsicle stick",
    "cigarette"
  ],
  "target": "D",
  "id": 0,
  "group_id": 0,
  "metadata": {
    "question_id": "22jbM6gDxdaMaunuzgrsBB",
    "direct_answers": "['cigarette', 'cigarette', 'cigarette', 'cigarette', 'cigarette', 'cigarette', 'cigarette', 'cigarette', 'cigarette', 'cigarette']",
    "difficult_direct_answer": false,
    "rationales": [
      "He's smoking while riding.",
      "The motorcyclist has a lit cigarette in his mouth while he rides on the street.",
      "The man is smoking."
    ]
  }
}

Prompt Template#

Prompt Template:

Answer the following multiple choice question. The last line of your response should be of the following format: 'ANSWER: [LETTER]' (without quotes) where [LETTER] is one of {letters}. Think step by step before answering.

{question}

{choices}

Usage#

Using CLI#

evalscope eval \
    --model YOUR_MODEL \
    --api-url OPENAI_API_COMPAT_URL \
    --api-key EMPTY_TOKEN \
    --datasets a_okvqa \
    --limit 10  # Remove this line for formal evaluation

Using Python#

from evalscope import run_task
from evalscope.config import TaskConfig

task_cfg = TaskConfig(
    model='YOUR_MODEL',
    api_url='OPENAI_API_COMPAT_URL',
    api_key='EMPTY_TOKEN',
    datasets=['a_okvqa'],
    limit=10,  # Remove this line for formal evaluation
)

run_task(task_cfg=task_cfg)