AI2D

Overview

AI2D (AI2 Diagrams) is a benchmark dataset for evaluating AI systems’ ability to understand and reason about scientific diagrams. It contains over 5,000 diverse diagrams from science textbooks covering topics like the water cycle, food webs, and biological processes.

Task Description

• Task Type: Diagram Understanding and Visual Reasoning

• Input: Scientific diagram image + multiple-choice question

• Output: Correct answer choice

• Domains: Science education, visual reasoning, diagram comprehension

Key Features

• Diagrams sourced from real science textbooks

• Requires joint understanding of visual layouts, symbols, and text labels

• Tests interpretation of relationships between diagram elements

• Multiple-choice format with challenging distractors

• Covers diverse scientific domains (biology, physics, earth science)

Evaluation Notes

• Default evaluation uses the test split

• Primary metric: Accuracy on multiple-choice questions

• Uses Chain-of-Thought (CoT) prompting for reasoning

• Requires understanding both textual labels and visual elements

Properties

Property	Value
Benchmark Name	ai2d
Dataset ID	lmms-lab/ai2d
Paper	N/A
Tags	Knowledge, MultiModal, QA
Metrics	acc
Default Shots	0-shot
Evaluation Split	test

Data Statistics

Metric	Value
Total Samples	3,088
Prompt Length (Mean)	324.64 chars
Prompt Length (Min/Max)	256 / 1024 chars

Image Statistics:

Metric	Value
Total Images	3,088
Images per Sample	min: 1, max: 1, mean: 1
Resolution Range	177x131 - 1500x1500
Formats	png

Sample Example

Subset: default

{
  "input": [
    {
      "id": "789e28fa",
      "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\nwhich of these define dairy item\n\nA) c\nB) D\nC) b\nD) a"
        },
        {
          "image": "[BASE64_IMAGE: png, ~226.2KB]"
        }
      ]
    }
  ],
  "choices": [
    "c",
    "D",
    "b",
    "a"
  ],
  "target": "B",
  "id": 0,
  "group_id": 0
}

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 ai2d \
    --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=['ai2d'],
    limit=10,  # Remove this line for formal evaluation
)

run_task(task_cfg=task_cfg)