datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
m_truthfulqa
Multilingual TruthfulQA
Dataset Summary
This dataset is a machine translated version of the TruthfulQA dataset, translated using GPT-3.5-turbo. This dataset was created by the University of Oregon, and was originally uploaded to this Github repository.
Citation
If you use this dataset in your work, please cite the following paper:
@article{dac2023okapi,
title={Okapi: Instruction-tuned Large Language Models in Multiple Languages with Reinforcement Learning… See the full description on the dataset page: https://huggingface.co/datasets/alexandrainst/m_truthfulqa.truthfulqa_true
Dataset Card for Dataset Name
Dataset Summary
This dataset card aims to be a base template for new datasets. It has been generated using this raw template.
Supported Tasks and Leaderboards
[More Information Needed]
Languages
[More Information Needed]
Dataset Structure
Data Instances
[More Information Needed]
Data Fields
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Data Splits
[More Information Needed]
Dataset Creation… See the full description on the dataset page: https://huggingface.co/datasets/v-xchen-v/truthfulqa_true.uhura-truthfulqa
Dataset Card for Uhura-TruthfulQA
Dataset Summary
TruthfulQA is a widely recognized safety benchmark designed to measure the truthfulness of language model outputs across 38 categories, including health, law, finance, and politics. The English version of the benchmark originates from TruthfulQA: Measuring How Models Mimic Human Falsehoods (Lin et al., 2022) and consists of 817 questions in both multiple-choice and generation formats, targeting common misconceptions and… See the full description on the dataset page: https://huggingface.co/datasets/masakhane/uhura-truthfulqa.truthfulqa-multi
Dataset Card for TruthfulQA-multi
TruthfulQA-multi is a professionally translated extension of the original TruthfulQA benchmark designed to evaluate truthfulness in Basque, Catalan, Galician, and Spanish. The dataset enables evaluating the ability of Large Language Models (LLMs) to maintain truthfulness across multiple languages.
Dataset Details
Dataset Description
TruthfulQA-multi extends the original English TruthfulQA dataset to four additional languages… See the full description on the dataset page: https://huggingface.co/datasets/HiTZ/truthfulqa-multi.X-TruthfulQA_en_zh_ko_it_es
X-TruthfulQA
🤗 Paper | 📖 arXiv
Dataset Description
X-TruthfulQA is an evaluation benchmark for multilingual large language models (LLMs), including questions and answers in 5 languages (English, Chinese, Korean, Italian and Spanish).
It is intended to evaluate the truthfulness of LLMs. The dataset is translated by GPT-4 from the original English-version TruthfulQA.
In our paper, we evaluate LLMs in a zero-shot generative setting: prompt the instruction-tuned LLM with… See the full description on the dataset page: https://huggingface.co/datasets/zhihz0535/X-TruthfulQA_en_zh_ko_it_es.truthfull_qa-trThis Dataset is part of a series of datasets aimed at advancing Turkish LLM Developments by establishing rigid Turkish benchmarks to evaluate the performance of LLM's Produced in the Turkish Language.
Dataset Card for truthful_qa-tr
malhajar/truthful_qa-tr is a translated version of truthful_qa aimed specifically to be used in the OpenLLMTurkishLeaderboard
Developed by: Mohamad Alhajar
Dataset Summary
TruthfulQA is a benchmark to measure whether a language model is… See the full description on the dataset page: https://huggingface.co/datasets/malhajar/truthfull_qa-tr.TruthReader_RAG_train
Dataset Card for TruthReader
This dataset is used to train the response generator in TruthReader framework.
Dataset information
type
language
Source
Annotator
#sample
Multi-document Synthesis
zh
WeiXin Articles
ChatGPT
387
Single-document Summary
zh,en
WeiXin Articles, Wikipedia
ChatGPT
561
QA Created
zh
Multi-domains
ChatGPT
1,482
WebCPM
zh
Web
Human
897
RefGPT
zh,en
Baidu Baike, Wikipedia
GPT-4
3,708
Dataset columns
The examples have… See the full description on the dataset page: https://huggingface.co/datasets/HIT-TMG/TruthReader_RAG_train.truthfulqa-multi-MT
Dataset Card for TruthfulQA-multi MT
TruthfulQA-multi is an automatically translated extension of the original TruthfulQA benchmark designed to evaluate truthfulness in Basque, Catalan, Galician, and Spanish. The dataset enables evaluating the ability of Large Language Models (LLMs) to maintain truthfulness across multiple languages.
Dataset Details
Dataset Description
TruthfulQA-multi extends the original English TruthfulQA dataset to four additional… See the full description on the dataset page: https://huggingface.co/datasets/HiTZ/truthfulqa-multi-MT.news-truthfulThis the dataset for Every Language Counts: Learn and Unlearn in Multilingual LLMs.
Each of the 100 row contains a GPT generated 'real' news article, a corresponding 'fake' news article with injected fake information, and the 'fake' keyword.
It contains 10 Q&A pairs on 'real' news for instruction tunning.
We also provide one question to evaluate 'real' news understanding and another question to count the appearance of 'fake' detail.
Note: The dataset contains news articles with fake… See the full description on the dataset page: https://huggingface.co/datasets/TaiMingLu/news-truthful.truthy-dpo-csvm_truthfulqa
Multilingual HellaSwag
Dataset Summary
This dataset is a machine translated version of the TruthfulQA dataset.
The languages was translated using GPT-3.5-turbo by the University of Oregon, and this part of the dataset was originally uploaded to this Github repository.
The NUS Deep Learning Lab contributed to this effort by standardizing the dataset, ensuring consistent question formatting and alignment across all languages. This standardization enhances cross-linguistic… See the full description on the dataset page: https://huggingface.co/datasets/richmondsin/m_truthfulqa.womens-health-benchmark-ground-truth
Womens Health Benchmark Ground Truth
A curated evaluation dataset for assessing large language models (LLMs) in womens health-related tasks. The dataset consists of model stumps paired with expert-written justifications describing observed errors.
Research Focus
This dataset supports structured evaluation of LLM behavior in clinically relevant womens health contexts, with emphasis on safety, reasoning quality, and evidence alignment.
Methodology
The dataset was… See the full description on the dataset page: https://huggingface.co/datasets/therubricai/womens-health-benchmark-ground-truth.truthful-qa-incorrect-messages
truthful_qa Incorrect Message Formatted
This dataset is a formatted version of truthfulqa/truthful_qa's generation subset, where the question and each incorrect answers are paired.
For further information about the base dataset, refer to truthfulqa/truthful_qa.
truthful_qa_CoT
Dataset Card for TruthfulQA-CoT
Dataset Details
Dataset Description
This dataset is an augmented version of TruthfulQA, where Chain-of-Thought (CoT) reasoning has been applied to the original questions. The dataset was generated using Camel-AI and GPT-4o Mini to enhance logical reasoning capabilities in smaller language models.
The dataset is valuable for fine-tuning smaller LLMs to improve CoT reasoning, helping models produce more structured and… See the full description on the dataset page: https://huggingface.co/datasets/0fg/truthful_qa_CoT.