datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
MMLU-SemiProThis dataset is derived from TIGER-Lab/MMLU-Pro as part of our MMLU-Leagues Encoder benchmark series, containing:
MMLU-Amateur, where the train set contains all questions Llama-3-8B-Instruct (5-shot) gets wrong and the test set contains all questions it gets right. The aim is to measure the ability of an encoder, with relatively limited training data, to match the performance of a small frontier model.
MMLU-SemiPro (this dataset), where the data is evenly split between a train and a test set.… See the full description on the dataset page: https://huggingface.co/datasets/answerdotai/MMLU-SemiPro.quran-question-answer-context
Dataset Card for "quran-question-answer-context"
Dataset Summary
Translated the original dataset from Arabic to English and added the Surah ayahs to the context column.
Usage
from datasets import load_dataset
dataset = load_dataset("nazimali/quran-question-answer-context")
DatasetDict({
train: Dataset({
features: ['q_id', 'question', 'answer', 'q_word', 'q_topic', 'fine_class', 'class', 'ontology_concept', 'ontology_concept2', 'source', 'q_src_id'… See the full description on the dataset page: https://huggingface.co/datasets/nazimali/quran-question-answer-context.enamed-2025-answers
ENAMED 2025 Answer Keys & Errata
Official answer key (Gabarito Oficial) and scoring metadata for INEP's ENAMED 2025 exam.
Dataset Summary
100 Answer Records matching IDs in gustavokch/enamed-2025.
Errata & Annulment Tracking: Includes is_annulled flag and errata notes.
Usage
from datasets import load_dataset
answers = load_dataset("gustavokch/enamed-2025-answers", split="test")
print(answers[0])
enamed-2025-booklet-2-answers
ENAMED 2025 (Caderno 2) Answer Keys & Official Gabarito Definitivo
Official final answer key (Gabarito Definitivo) and scoring metadata for INEP's ENAMED 2025 exam (Booklet 2 / Caderno 02).
Dataset Summary
100 Answer Records matching IDs in gustavokch/enamed-2025-booklet-2.
Gabarito Definitivo & Annulments: Incorporates all 10 official post-appeal question annulments (is_annulled: true, answer_index: -1).
Usage
from datasets import load_dataset… See the full description on the dataset page: https://huggingface.co/datasets/gustavokch/enamed-2025-booklet-2-answers.arabic_dialects_question_and_answerData Content
The file provided: Q/A Reasoning dataset
contains the following columns:
ID # : Denotes the reference ID for:
a. Question
b. Answer to the question
c. Hint
d. Reasoning
e. Word count for items a to d above
Dialects: Contains the following dialects in separate columns:
a. English
b. MSA
c. Emirati
d. Egyptian
e. Levantine Syria
f. Levantine Jordan
g. Levantine Palestine
h. Levantine Lebanon
Data Generation Process
The following are the steps that were followed to curate the data:… See the full description on the dataset page: https://huggingface.co/datasets/CNTXTAI0/arabic_dialects_question_and_answer.answers-with-receipts
Answers with Receipts
26 real customer-support questions, each answered by an autonomous AI agent that paid its own money to compete, and each answer approved by the business that asked the question. Every row carries the on-chain transaction that paid the agent.
The preference label in this dataset is backed by a payment, not a click.
Why this is unusual
Most human-feedback datasets label a preference with an annotator's click. A click is cheap and reversible… See the full description on the dataset page: https://huggingface.co/datasets/deskcrew/answers-with-receipts.yuitc-legal-gold-answer
YuITC Vietnamese Legal Gold Answer Dataset (100 samples)
Tập dữ liệu Gold Answer gồm 100 câu hỏi được kiểm định nghiêm ngặt từ benchmark YuITC/Vietnamese-Legal-Documents.
Schema 6 cột
id: ID thứ tự từ 1 đến 100
qid: ID câu hỏi gốc
question: Nội dung câu hỏi
cid: ID đoạn văn bản liên quan (nếu có)
context_list: Danh sách các văn bản pháp luật căn cứ
answer: Đáp án tham chiếu (Gold Answer) trung thành với văn bản
Repository URL:… See the full description on the dataset page: https://huggingface.co/datasets/juzharii/yuitc-legal-gold-answer.llm-answer-set-qa
Answer-Set Consistency Benchmark (ASCB)
Overview
The Answer-Set Consistency Benchmark (ASCB) evaluates whether language models provide mutually consistent answers to related factual enumeration questions. Unlike conventional QA datasets, ASCB focuses on whether generated answer sets satisfy known set-theoretic relations rather than solely on factual accuracy.
ASCB contains 600 English question quadruples (2,400 questions) across primarily static, objective factual… See the full description on the dataset page: https://huggingface.co/datasets/anonymous2026nips/llm-answer-set-qa.MMLU-AmateurThis dataset is derived from TIGER-Lab/MMLU-Pro as part of our MMLU-Leagues Encoder benchmark series, containing:
MMLU-Amateur (this dataset), where the train set contains all questions Llama-3-8B-Instruct (5-shot) gets wrong and the test set contains all questions it gets right. The aim is to measure the ability of an encoder, with relatively limited training data, to match the performance of a small frontier model.
MMLU-SemiPro, where the data is evenly split between a train and a test set.… See the full description on the dataset page: https://huggingface.co/datasets/answerdotai/MMLU-Amateur.Islam_Question_and_Answer1religious-questions-and-answers
Main fields
article_id, url, title, question, short_answer, content_html,
content_text, published_at_persian, view_count, and category fields.
is_valid_article marks archive links that resolved to a valid article page.