datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
ChatGPT-Jailbreak-Prompts
Dataset Card for Dataset Name
Name
ChatGPT Jailbreak Prompts
Dataset Summary
ChatGPT Jailbreak Prompts is a complete collection of jailbreak related prompts for ChatGPT. This dataset is intended to provide a valuable resource for understanding and generating text in the context of jailbreaking in ChatGPT.
Languages
[English]
RubricHub_v1
RubricHub
RubricHub is a large-scale (approximately 110K), multi-domain dataset that provides high-quality rubric-based supervision for open-ended generation tasks. It is constructed via an automated coarse-to-fine rubric generation framework, which integrates principle-guided synthesis, multi-model aggregation, and difficulty evolution to produce comprehensive and highly discriminative evaluation criteria, overcoming the supervision ceiling of… See the full description on the dataset page: https://huggingface.co/datasets/sojuL/RubricHub_v1.ru-bank-ie
pymlex/ru-bank-ie
Russian bank client information extraction benchmark with coverage-validated text-to-JSON pairs.
Each example contains a chat-style client message, a gold BankClientExtraction JSON object,
and a separate validation_json coverage justification. Fields may be null when absent from the source text.
Columns
id — sample identifier
reasoning — model planning before the client message
text — client message used for evaluation
gold_json — gold… See the full description on the dataset page: https://huggingface.co/datasets/pymlex/ru-bank-ie.Rubric-Graded-Reasoning
Rubrics-Graded Reasoning — Computer Science, Data Science, Chemistry
A multi-domain reasoning dataset built to improve frontier models by revealing their failures and turning expert grading into training signal.
The dataset pairs self-contained tasks with weighted rubrics across three domains — Computer Science, Data Science, and Chemistry — turning expert evaluation into training signals that boost frontier-model reasoning.
Explore the full Rubric-based reasoning data pack:… See the full description on the dataset page: https://huggingface.co/datasets/TuringEnterprises/Rubric-Graded-Reasoning.GammaCorpus-Fact-QA-450k
GammaCorpus: Fact QA 450k
What is it?
GammaCorpus Fact QA 450k is a dataset that consists of 450,000 fact-based question-and-answer pairs designed for training AI models on factual knowledge retrieval and question-answering tasks.
Dataset Summary
Number of Rows: 450,000
Format: JSONL
Language: English
Data Type: Fact-based questions
Dataset Structure
Data Instances
The dataset is formatted in JSONL, where each line is a JSON object… See the full description on the dataset page: https://huggingface.co/datasets/rubenroy/GammaCorpus-Fact-QA-450k.RuBQ_2.0
RuBQ 2.0
For training data see d0rj/RuBQ_2.0-paragraphs.
APTER-Rubrics
APTER Expert-Grounded Query-Level Rubrics
This dataset contains the query-level Rubrics from APTER: Adaptive
Post-Training with Expert-Grounded Rubrics for mathematical reasoning and
medical question answering. Each Rubric instantiates an expert-defined
criterion into a fine-grained requirement for a specific query.
Technical report: arXiv:2608.14212
Project repository: AntDT-APTER/APTER
Data
Split
Queries
Rubric items
math
16,755
67,817
medical
28… See the full description on the dataset page: https://huggingface.co/datasets/AntDT-APTER/APTER-Rubrics.llm-metric-mmluRubricHub_v1
RubricHub_v1
RubricHub is a large-scale (approximately 110K), multi-domain dataset that provides high-quality rubric-based supervision for open-ended generation tasks. It is constructed via an automated coarse-to-fine rubric generation framework, which integrates principle-guided synthesis, multi-model aggregation, and difficulty evolution to produce comprehensive and highly discriminative evaluation criteria, overcoming the supervision ceiling of coarse or static rubrics.… See the full description on the dataset page: https://huggingface.co/datasets/rico2512/RubricHub_v1.RubricHub_v1
RubricHub
RubricHub is a large-scale (approximately 110K), multi-domain dataset that provides high-quality rubric-based supervision for open-ended generation tasks. It is constructed via an automated coarse-to-fine rubric generation framework, which integrates principle-guided synthesis, multi-model aggregation, and difficulty evolution to produce comprehensive and highly discriminative evaluation criteria, overcoming the supervision ceiling of… See the full description on the dataset page: https://huggingface.co/datasets/dans25275/RubricHub_v1.RubricHub_v1
RubricHub_v1
RubricHub is a large-scale (approximately 110K), multi-domain dataset that provides high-quality rubric-based supervision for open-ended generation tasks. It is constructed via an automated coarse-to-fine rubric generation framework, which integrates principle-guided synthesis, multi-model aggregation, and difficulty evolution to produce comprehensive and highly discriminative evaluation criteria, overcoming the supervision ceiling of coarse or static rubrics.… See the full description on the dataset page: https://huggingface.co/datasets/0xzanuee/RubricHub_v1.AVQA-Audio-Rubrics
AVQA Audio-Reasoning Rubrics
Project Page | Paper | Code
Audio-grounded, binary-evaluable evaluation rubrics for the full
AVQA training set, generated for
process-level reward modeling in audio reasoning RL (e.g. GRPO / RLHF with
rubric-as-reward).
Each training question is annotated with 5 rubrics, one per evaluation
facet, that judge the quality of an audio-reasoning response — not just final
answer correctness. The rubrics are designed to be scored Yes/No by an
LLM judge that… See the full description on the dataset page: https://huggingface.co/datasets/umd-zhou-lab/AVQA-Audio-Rubrics.ChatGPT-Jailbreak-Prompts-rubend18
Dataset Card for Dataset Name
Name
ChatGPT Jailbreak Prompts
Dataset Summary
ChatGPT Jailbreak Prompts is a complete collection of jailbreak related prompts for ChatGPT. This dataset is intended to provide a valuable resource for understanding and generating text in the context of jailbreaking in ChatGPT.
Languages
[English]
rubai-text-s60m
Uzbek Informative Text Dataset
A large-scale, high-quality dataset of informative text passages in Uzbek language (Latin script), synthetically generated through knowledge distillation from a state-of-the-art large language model.
Support my works and open-source movement: https://tirikchilik.uz/islomovs
Dataset Summary
This dataset contains 1,140,910 rows of educational and informative text passages covering 80 diverse topics and 640 subtopics. Each entry pairs a… See the full description on the dataset page: https://huggingface.co/datasets/islomov/rubai-text-s60m.RubricHub_v1
RubricHub_v1
RubricHub is a large-scale (approximately 110K), multi-domain dataset that provides high-quality rubric-based supervision for open-ended generation tasks. It is constructed via an automated coarse-to-fine rubric generation framework, which integrates principle-guided synthesis, multi-model aggregation, and difficulty evolution to produce comprehensive and highly discriminative evaluation criteria, overcoming the supervision ceiling of coarse or static rubrics.… See the full description on the dataset page: https://huggingface.co/datasets/longta1998/RubricHub_v1.RubricHub_v1
RubricHub
RubricHub is a large-scale (approximately 110K), multi-domain dataset that provides high-quality rubric-based supervision for open-ended generation tasks. It is constructed via an automated coarse-to-fine rubric generation framework, which integrates principle-guided synthesis, multi-model aggregation, and difficulty evolution to produce comprehensive and highly discriminative evaluation criteria, overcoming the supervision ceiling of… See the full description on the dataset page: https://huggingface.co/datasets/yudhabanguni/RubricHub_v1.RubricHub_v1
RubricHub
RubricHub is a large-scale (approximately 110K), multi-domain dataset that provides high-quality rubric-based supervision for open-ended generation tasks. It is constructed via an automated coarse-to-fine rubric generation framework, which integrates principle-guided synthesis, multi-model aggregation, and difficulty evolution to produce comprehensive and highly discriminative evaluation criteria, overcoming the supervision ceiling of… See the full description on the dataset page: https://huggingface.co/datasets/anh013/RubricHub_v1.GammaCorpus-Math-QA-2m
GammaCorpus: Math QA 2m
What is it?
GammaCorpus Math QA 2m is a dataset that consists of 2,760,000 mathematical question-and-answer. It consists of 917,196 addition questions, 916,662 subtraction questions, 917,015 multiplication questions, and 9,126 division questions.
Dataset Summary
Number of Rows: 2,760,000
Format: JSONL
Data Type: Mathematical Question Pairs
Dataset Structure
Data Instances
The dataset is formatted in JSONL, where… See the full description on the dataset page: https://huggingface.co/datasets/rubenroy/GammaCorpus-Math-QA-2m.InteractComp
InteractComp (Encrypted Release)
InteractComp accompanies the paper "INTERACTCOMP: Evaluating Search Agents with Ambiguous Queries" (Deng et al., 2025). The benchmark targets a capability gap in modern search agents: recognizing ambiguity, asking clarifying questions, and only then executing retrieval or answering. Despite rapid progress on fully specified web queries, the paper shows that interaction-centric performance remains stagnant—highlighting InteractComp as both an… See the full description on the dataset page: https://huggingface.co/datasets/Rubbisheep/InteractComp.ChatGPT-Jailbreak-Prompts-rubend18
Dataset Card for Dataset Name
Name
ChatGPT Jailbreak Prompts
Dataset Summary
ChatGPT Jailbreak Prompts is a complete collection of jailbreak related prompts for ChatGPT. This dataset is intended to provide a valuable resource for understanding and generating text in the context of jailbreaking in ChatGPT.
Languages
[English]
RuBQ_1.0
RuBQ 1.0
RuBQ_2.0-paragraphs
RuBQ_2.0-paragraphs
For test and dev data see d0rj/RuBQ_2.0
RubricHub_v1_config
RubricHub
RubricHub is a large-scale (approximately 110K), multi-domain dataset that provides high-quality rubric-based supervision for open-ended generation tasks. It is constructed via an automated coarse-to-fine rubric generation framework, which integrates principle-guided synthesis, multi-model aggregation, and difficulty evolution to produce comprehensive and highly discriminative evaluation criteria, overcoming the supervision ceiling of… See the full description on the dataset page: https://huggingface.co/datasets/NovelHacja/RubricHub_v1_config.