datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
task_data
QuantCodeEval
A benchmark for evaluating LLM coding agents on quantitative-strategy code
reproduction from finance research papers.
Status: Anonymous artifact for the 30-task benchmark.
Release mirrors
The release is mirrored at two anonymous locations:
Hugging Face Datasets — complete anonymous release:
https://huggingface.co/datasets/quantcodeeval/task_data
anonymous.4open.science — browseable mirror:
https://anonymous.4open.science/r/QuantCodeEval-Anonymous… See the full description on the dataset page: https://huggingface.co/datasets/quantcodeeval/task_data.rna-downstream-tasks
GB.RNA Benchmark Datasets
mRNA related tasks
Translation efficiency prediction from Chu et al.(2024) [1]
3 cell lines: Muscle, pc3, HEK
input sequence: 5'UTR
10-fold cross-validation split
mRNA expression level prediction from Chu et al.(2024) [1]
3 cell lines: Muscle, pc3, HEK
input sequence: 5'UTR
10-fold cross-validation split
Mean ribosome load prediction from Sample et al. (2019) [2]
input sequence: 5'UTR
ouput: mean ribosome load
the original data… See the full description on the dataset page: https://huggingface.co/datasets/genbio-ai/rna-downstream-tasks.jigsaw_toxicityblog_authorship_corpussocial-chemestry-101task-matchessimlexbuat-task-2winowhyhttps://github.com/HKUST-KnowComp/WinoWhy
@inproceedings{zhang2020WinoWhy,
author = {Hongming Zhang and Xinran Zhao and Yangqiu Song},
title = {WinoWhy: A Deep Diagnosis of Essential Commonsense Knowledge for Answering Winograd Schema Challenge},
booktitle = {Proceedings of Annual Meeting of the Association for Computational Linguistics (ACL) 2020},
year = {2020}
}
Reverse-alpha-suppression-task-boostOriginal-alpha-suppression-task-boostosworld_tasks_filesate-task-ability-dataset
O*NET Task-to-Ability Mapping Dataset
A task-level mapping from 18,796 O*NET work tasks, spanning all 23 SOC major groups (economy-wide), to the 52 O*NET human abilities each task requires, with a graded importance weight per (task, ability) pair. The dataset contains 95,330 task-to-ability mappings.
It was built as the empirical foundation for the ATES (Agentic Task Exposure Score) framework, but stands alone for research on skill demand, automation exposure, and the division… See the full description on the dataset page: https://huggingface.co/datasets/ravishgupta/ate-task-ability-dataset.paradehttps://github.com/heyunh2015/PARADE_dataset
@inproceedings{he-etal-2020-parade,
title = "{PARADE}: {A} {N}ew {D}ataset for {P}araphrase {I}dentification {R}equiring {C}omputer {S}cience {D}omain {K}nowledge",
author = "He, Yun and
Wang, Zhuoer and
Zhang, Yin and
Huang, Ruihong and
Caverlee, James",
booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)",
month = nov,
year = "2020",
address… See the full description on the dataset page: https://huggingface.co/datasets/tasksource/parade.COLING-2025-CHIPSAL
Dataset Card for Dataset Name
This dataset card aims to be a base template for new datasets. It has been generated using this raw template.
Dataset Details
Dataset Description
Curated by: [More Information Needed]
Funded by [optional]: [More Information Needed]
Shared by [optional]: [More Information Needed]
Language(s) (NLP): [More Information Needed]
License: [More Information Needed]
Dataset Sources [optional]
Repository: [More… See the full description on the dataset page: https://huggingface.co/datasets/1-800-SHARED-TASKS/COLING-2025-CHIPSAL.osworld_tasks_filesBAREC-Shared-Task-2025-sent
BAREC Shared Task 2025
Dataset Summary
BAREC (the Balanced Arabic Readability Evaluation Corpus) is a large-scale dataset developed for the BAREC Shared Task 2025, focused on fine-grained Arabic readability assessment. The dataset includes over 1M words, annotated across 19 readability levels, with additional mappings to coarser 7, 5, and 3 level schemes.
The dataset is annotated at the sentence level. Document-level readability scores are derived by assigning each… See the full description on the dataset page: https://huggingface.co/datasets/CAMeL-Lab/BAREC-Shared-Task-2025-sent.GPU-Resources-Estimation-for-Deep-Learning-Training-Tasks
GPUMemNet and GPUUtilNet Dataset
This dataset accompanies the paper
“GPU Memory and Utilization Estimation for Training-Aware Resource
Management: Opportunities and Limitations.”
It contains synthetic deep learning training configurations and their measured
GPU memory consumption and utilization characteristics.
Dataset configurations
The dataset is divided into separate configurations because MLP, CNN, and
Transformer workloads use different feature schemas.… See the full description on the dataset page: https://huggingface.co/datasets/ehyo/GPU-Resources-Estimation-for-Deep-Learning-Training-Tasks.monotonicity-entailment@inproceedings{yanaka-etal-2019-neural,
title = "Can Neural Networks Understand Monotonicity Reasoning?",
author = "Yanaka, Hitomi and
Mineshima, Koji and
Bekki, Daisuke and
Inui, Kentaro and
Sekine, Satoshi and
Abzianidze, Lasha and
Bos, Johan",
booktitle = "Proceedings of the 2019 ACL Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP",
year = "2019",
pages = "31--40",
}
BAREC-Shared-Task-2025-doc
BAREC Shared Task 2025
Dataset Summary
BAREC (the Balanced Arabic Readability Evaluation Corpus) is a large-scale dataset developed for the BAREC Shared Task 2025, focused on fine-grained Arabic readability assessment. The dataset includes over 1M words, annotated across 19 readability levels, with additional mappings to coarser 7, 5, and 3 level schemes.
The dataset is annotated at the sentence level. Document-level readability scores are derived by assigning each… See the full description on the dataset page: https://huggingface.co/datasets/CAMeL-Lab/BAREC-Shared-Task-2025-doc.legal-time-entry-billing-task-scope-coherence-risk-v0.1What this dataset does
You receive
engagement scope
fee terms
time entries
file activity
red flags
You decide
coherent
or
incoherent
Daily use
invoice QA
stop vague billing
scope creep detection
reduce fee challenges
SemEval-2021-Task-7-JokesAn unmodified copy of the datasets contained in the github repo "hahackathon-2021", which can be found here. Several other Github repositories include copies of this dataset, but I've linked the specific repository I found first.
Includes the following datasets:
hahackathon_dev.csv
hahackathon_test.csv
hahackathon_train.csv
The former two do not include any information other than the joke text and a unique ID, unfortunately. I'm not sure where the rest of the data is published, if at all… See the full description on the dataset page: https://huggingface.co/datasets/hfht/SemEval-2021-Task-7-Jokes.Gemini_3.1_202_Task_AI_Exposure_Scores
Gemini 3.1 2026 Task AI Exposure Scores
Dataset Summary
This dataset contains task-level AI exposure labels for O*NET task statements. Each task is classified into one of four categories, E0, E1, E2, or E3, using an updated 2026 Agentic AI Exposure Rubric and a Gemini 3.1 Pro classification pipeline. The labels are designed to capture whether a task can be accelerated by a frontier agentic AI system directly, whether it would require deeper software integration, or… See the full description on the dataset page: https://huggingface.co/datasets/MIT-WAL/Gemini_3.1_202_Task_AI_Exposure_Scores.english-gradinghttps://www.kaggle.com/competitions/feedback-prize-english-language-learning
sts-companionhttps://ixa2.si.ehu.eus/stswiki/index.php/STSbenchmark
The companion datasets to the STS Benchmark comprise the rest of the English datasets used in the STS tasks organized by us in the context of SemEval between 2012 and 2017.
Authors collated two datasets, one with pairs of sentences related to machine translation evaluation. Another one with the rest of datasets, which can be used for domain adaptation studies.
@inproceedings{cer-etal-2017-semeval,
title = "{S}em{E}val-2017 Task 1:… See the full description on the dataset page: https://huggingface.co/datasets/tasksource/sts-companion.some-task-582d4e
some-task-582d4e
Synthetic weather test data: 48 rows in data.csv.
All values are randomly generated fictional examples, not real observations, products, or user activity. Intended only for CSV loading and pipeline tests; not suitable for scientific or business conclusions. Columns are sampled independently and do not model real-world correlations.
Fields
sample_id: random identifier for this generated sample.
row_id: sequential row number starting at 1.… See the full description on the dataset page: https://huggingface.co/datasets/browntimothy/some-task-582d4e.osworld_tasks_filesRadNLP2024_sub_task
RadNLP 2024 sub task: Document Segmentation for Lung Cancer Staging
📜 Paper
📚 Introduction
RadNLP 2024 is a shared task in the international conference NTCIR-18, organized by the National Institute of Informatics in Japan.
Management of lung cancer is based on the stage, and radiology reports provide various related information by describing medical images such as CT and MRI.
However, radiology reports do not always specify the stage explicitly¹.… See the full description on the dataset page: https://huggingface.co/datasets/RadNLP/RadNLP2024_sub_task.context_toxicityhttps://github.com/ipavlopoulos/context_toxicity/
@inproceedings{xenos-etal-2021-context,
title = "Context Sensitivity Estimation in Toxicity Detection",
author = "Xenos, Alexandros and
Pavlopoulos, John and
Androutsopoulos, Ion",
booktitle = "Proceedings of the 5th Workshop on Online Abuse and Harms (WOAH 2021)",
month = aug,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url =… See the full description on the dataset page: https://huggingface.co/datasets/tasksource/context_toxicity.genshin-impact-task-dialogue