Auto57%Harbor: pendingMultimodalMath

PlotGround-1k

PlotGround: Grounding Plot Digitization in Real Scientific Figures and Their Source Data

A human-verified benchmark of 1,119 quantitative questions from 1,066 bioRxiv preprints measuring plot digitization accuracy using real figures and source data.

How to run

ltb · plotground-1k
$ npm i -g lettokenburn-cli
$ ltb bench info plotground-1k

External harness. No Harbor adapter has been generated for this benchmark yet. `ltb bench info` prints the known links.

Runs happen on your machine with your own subscription; only the score summary is pushed. CLI docs

Scores

16 sourced entries
HarnessSourceConfidenceLink
GPT-5.6 Sol73.8N/AIndependentmediumOct 5, 2026arxiv.org
GPT-5.6 Luna69.7N/AIndependentmediumOct 5, 2026arxiv.org
GPT-5.6-terra66.6N/AIndependentmediumOct 5, 2026arxiv.org
Gemini 3.7 Flash65.7N/AIndependentmediumOct 5, 2026arxiv.org
Gemini 3.8 Flash65.5N/AIndependentmediumOct 5, 2026arxiv.org
Claude Opus 560.2N/AIndependentmediumOct 5, 2026arxiv.org
Qwen3.8 Max57.7N/AIndependentmediumOct 5, 2026arxiv.org
Claude Sonnet 555.6N/AIndependentmediumOct 5, 2026arxiv.org
Gemini 3.1 Pro49.9N/AIndependentmediumOct 5, 2026arxiv.org
Qwen3.8 Flash42.6N/AIndependentmediumOct 5, 2026arxiv.org
GLM-5.3 Flash39.8N/AIndependentmediumOct 5, 2026arxiv.org
Kimi K338.2N/AIndependentmediumOct 5, 2026arxiv.org
MiniMax-M333.8N/AIndependentmediumOct 5, 2026arxiv.org
Inkling32.0N/AIndependentmediumOct 5, 2026arxiv.org
DeepSeek V4.1 Flash29.3N/AIndependentmediumOct 5, 2026arxiv.org
DeepSeek V4 FV exp17.0N/AIndependentmediumOct 5, 2026arxiv.org

Every number links to where it was published. Low-confidence rows are muted and need per-cell verification.

Reproduced by the community

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About

PlotGround-1k consists of 1,119 questions derived from real scientific figures in bioRxiv preprints, grounded by author-released source data. It uses an automated pipeline to map figures to source tables and generate quantitative questions.

Scoring uses relative-error tolerance (±5% or ±2%). The best model achieved 87.5% accuracy at ±5% tolerance, with significant drops at stricter tolerances, highlighting a precision gap in visual numerical recovery.