Repo · Benchmarks & research
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Standardizes hundreds of public datasets into interchangeable multiple-choice, classification, and token-classification templates, and…
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Datasets collection and preprocessings framework for NLP extreme multitask learning
benchmarkbigbenchcurated-datasetsdataset-collectiondecision-modeldecision-modelsdiscriminativeextreme-mtlextreme-multi-task-learninginstruction-tuningmeta-learningmulti-task-learningmulti-task-learning-scalingnatural-language-inferencenlppreprocessingsreward-modelingscalingtext-classification
How builders describe it
Standardizes hundreds of public datasets into interchangeable multiple-choice, classification, and token-classification templates, and deterministically recasts them into typed choice, score, and noul decision requests.
The decision Jev makes
Benchmark questions with known answers, to check accuracy and confidence.
Where it fits
Head-to-head tests, calibration studies and independent research into how well Jev decides, how fast, and at what cost. All 682 benchmarks & research projects →
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