Datasets › ScienceQA

ScienceQA (Science Question Answering)

Introduced by Pan Lu et al. in Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering20 Sep 2022 archive 2025-07-28

Science Question Answering (ScienceQA) is a new benchmark that consists of 21,208 multimodal multiple choice questions with diverse science topics and annotations of their answers with corresponding lectures and explanations. Out of the questions in ScienceQA, 10,332 (48.7%) have an image context, 10,220 (48.2%) have a text context, and 6,532 (30.8%) have both. Most questions are annotated with grounded lectures (83.9%) and detailed explanations (90.5%). The lecture and explanation provide general external knowledge and specific reasons, respectively, for arriving at the correct answer. To the best of our knowledge, ScienceQA is the first large-scale multimodal dataset that annotates lectures and explanations for the answers.

ScienceQA, in contrast to previous datasets, has richer domain diversity from three subjects: natural science, language science, and social science. Questions in each subject are categorized first by the topic (Biology, Physics, Chemistry, etc.), then by the category (Plants, Cells, Animals, etc.), and finally by the skill (Classify fruits and vegetables as plant parts, Identify countries of Africa, etc.). ScienceQA features 26 topics, 127 categories, and 379 skills that cover a wide range of domains.

Benchmarks archive 2025-07-28

All 1 leaderboard whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.

First row (archive order)PaperCode
Science Question Answering ScienceQA MC-CoT F-Large Avg. Accuracy 94.88 Boosting the Power of Small Multimodal Reasoning Models... chengtan9907/mc-cot 10 Compare

Papers archive 2025-07-28

6 shown of 6 papers with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 339. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.

DateSamples run Syntology
Video-LaVIT: Unified Video-Language Pre-training with Decoupled Visual-Motional Tokenization 1 1 5 Feb 2024 ran 3 of 5 samples (2 unverified; 5 pointer-only for licence)
Honeybee: Locality-enhanced Projector for Multimodal LLM 1 1 11 Dec 2023 ran 3 of 3 samples (0 unverified; 3 pointer-only for licence)
Boosting the Power of Small Multimodal Reasoning Models to Match Larger Models with Self-Consistency Training 1 1 23 Nov 2023 ran 1 of 1 samples (0 unverified; 1 pointer-only for licence)
Chat-UniVi: Unified Visual Representation Empowers Large Language Models with Image and Video Understanding 4 1 14 Nov 2023 not harvested
Multimodal Chain-of-Thought Reasoning in Language Models 3 1 2 Feb 2023 ran 6 of 11 samples (5 unverified; 1 pointer-only for licence)
Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering 1 4 20 Sep 2022 ran 4 of 5 samples (1 unverified; 2 pointer-only for licence)

Dataset loaders archive 2025-07-28

4 loaders as listed in the archive; links are outbound and not re-checked here.

Tasks archive 2025-07-28

License archive 2025-07-28

CC BY-NC-SA

Modalities archive 2025-07-28

Languages archive 2025-07-28

Variants archive 2025-07-28

  • ScienceQA

1 variant name, as the archive lists them.

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