ScienceQA

ScienceQA is the first large-scale multimodal science question answering benchmark with 21,208 multiple-choice questions covering 3 subjects (natural science, language science, social science), 26 topics, 127 categories, and 379 skills. The benchmark includes both text and image modalities, featuring detailed explanations and Chain-of-Thought reasoning to diagnose multi-hop reasoning ability.

Phi-3.5-vision-instruct from Microsoft currently leads the ScienceQA leaderboard with a score of 0.913 across 1 evaluated AI models.

Paper

MicrosoftPhi-3.5-vision-instruct leads with 91.3%.

Progress Over Time

Interactive timeline showing model performance evolution on ScienceQA

State-of-the-art frontier
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ScienceQA Leaderboard

1 models
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FAQ

Common questions about ScienceQA.

What is the ScienceQA benchmark?

ScienceQA is the first large-scale multimodal science question answering benchmark with 21,208 multiple-choice questions covering 3 subjects (natural science, language science, social science), 26 topics, 127 categories, and 379 skills. The benchmark includes both text and image modalities, featuring detailed explanations and Chain-of-Thought reasoning to diagnose multi-hop reasoning ability.

What is the ScienceQA leaderboard?

The ScienceQA leaderboard ranks 1 AI models based on their performance on this benchmark. Currently, Phi-3.5-vision-instruct by Microsoft leads with a score of 0.913. The average score across all models is 0.913.

What is the highest ScienceQA score?

The highest ScienceQA score is 0.913, achieved by Phi-3.5-vision-instruct from Microsoft.

How many models are evaluated on ScienceQA?

1 models have been evaluated on the ScienceQA benchmark, with 0 verified results and 1 self-reported results.

Where can I find the ScienceQA paper?

The ScienceQA paper is available at https://arxiv.org/abs/2209.09513. The paper details the methodology, dataset construction, and evaluation criteria.

What categories does ScienceQA cover?

ScienceQA is categorized under math, multimodal, reasoning, and vision. The benchmark evaluates multimodal models.

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