datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
SciKnowEval
SciKnowEval
Evaluating Multi-level Scientific Knowledge of Large Language Models
Please refer to our repository and paper for more details.
博学之 ，审问之 ，慎思之 ，明辨之 ，笃行之。
—— 《礼记 · 中庸》 Doctrine of the Mean
The Scientific Knowledge Evaluation (SciKnowEval) benchmark for Large Language Models (LLMs) is inspired by the profound principles outlined in the “Doctrine of the Mean” from ancient Chinese philosophy. This benchmark is designed to assess LLMs based on their proficiency in… See the full description on the dataset page: https://huggingface.co/datasets/hicai-zju/SciKnowEval.SciKnowEval_mcqa
Dataset Card for SciKnowEval_mcqa
Dataset Description
This dataset is a modified version of the original SciKnowEval dataset.
SciKnowEval is a comprehensive dataset designed to evaluate the scientific knowledge reasoning capabilities of Large Language Models (LLMs). It spans primarily across a few domains (Physics, Chemistry, Biology, Materials).
Modifications in this Version
In this release, we have curated this dataset to focus only on MCQA questions… See the full description on the dataset page: https://huggingface.co/datasets/ShAIkespear/SciKnowEval_mcqa.sciknoweval_l3SciKnowEval
SciKnowEval
Evaluating Multi-level Scientific Knowledge of Large Language Models
Please refer to our repository and paper for more details.
博学之 ，审问之 ，慎思之 ，明辨之 ，笃行之。
—— 《礼记 · 中庸》 Doctrine of the Mean
The Scientific Knowledge Evaluation (SciKnowEval) benchmark for Large Language Models (LLMs) is inspired by the profound principles outlined in the “Doctrine of the Mean” from ancient Chinese philosophy. This benchmark is designed to assess LLMs based on their proficiency in… See the full description on the dataset page: https://huggingface.co/datasets/Xh1Xxhg/SciKnowEval.sciknoweval_l3sciKnowEval-OESciKnowEval
SciKnowEval — evaluation data (OpenCompass format)
Bud Ecosystem eval mirror (config SciKnowEval_gen). Source hicai-zju/SciKnowEval — license MIT, unchanged; all rights remain with the original authors.
sciknoweval-v2-hard-autogradable-512-2026-04-28
SciKnowEval v2 Hard Autogradable 512 - 2026-04-28
A 512-example sanity subset sampled from hicai-zju/SciKnowEval (v2, test) for Plan-CRL scientific reasoning evals.
Selection seed: 20260428.
Filtering and balancing:
excludes L1
keeps L2, L3, L4
keeps autogradable types: mcq-4-choices, mcq-2-choices, true_or_false, filling
requires answerKey or answer
balances domains at 128 examples each: Biology, Chemistry, Material, Physics
per domain: 32 L2, 48 L3, 48 L4
Useful fields for… See the full description on the dataset page: https://huggingface.co/datasets/1337xyz1337xyz/sciknoweval-v2-hard-autogradable-512-2026-04-28.olmo_sft_sciknoweval_testSciknoweval-mcqa_Turkish
Translated with: Karga-DPO-v0.1
Broken translations were cleaned off. Beware of hallucinations though.
sciknoweval