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Few-Shot Learning datasets

archive 2025-07-28

45 datasets carry the task tag "Few-Shot Learning" (the task itself: Few-Shot Learning), ordered by the archive's paper count. Page 1 of 1: 45 shown of 45. Facet routes are this site's own (the archive records the tag string, not a page).

The archive holds 12,214 dataset rows; 12,172 are listed. 6 are withheld from every listing and count here as vandalised before snapshot (6 with contact-centre spam in the title, 0 with a spam description on a row that has no homepage, no paper and no papers counted; none with more than 1 paper, 0 with a benchmark), listed in withheld.json; 1 listed row carries a vandalised description, withheld on its page. This gate never withholds a row with a homepage or a paper that resolves, and a clean description; the content rules below withhold a row whose name is spam whatever else it carries. The gate is a phrase list: these are the rows it caught, not a claim that the rest is clean. Before that gate, the site's content rules withhold 36 more rows (invite-code, gambling, travel-booking, contact-centre and similar spam in the name or on a row with nothing real behind it); they have no page and are listed in withheld.json.

Few-Shot Learning datasets 1–45 of 45

ImageNet

The ImageNet dataset contains 14,197,122 annotated images according to the WordNet hierarchy.

Images Image Classification Classification Image Generation Zero-Shot Learning Visual Question Answering (VQA)Few-Shot Image Classification+37 tasks

15,430 papers · 52 benchmarks

GLUE (General Language Understanding Evaluation benchmark)

General Language Understanding Evaluation (GLUE) benchmark is a collection of nine natural language understanding tasks, including single-sentence tasks CoLA and SST-2, similarity and paraphrasing tasks MRPC, STS-B and QQP, and natural…

Texts Classification Text Classification Text Generation Few-Shot Learning Natural Language Inference Semantic Textual Similarity+8 tasks

3,197 papers · 13 benchmarks

SST (Stanford Sentiment Treebank)

The Stanford Sentiment Treebank is a corpus with fully labeled parse trees that allows for a complete analysis of the compositional effects of sentiment in language.

Texts Classification Text Classification Sentiment Analysis Few-Shot Learning Out-of-Distribution Detection Few-Shot Text Classification+2 tasks

2,354 papers · 6 benchmarks

CUB-200-2011 (Caltech-UCSD Birds-200-2011)

The Caltech-UCSD Birds-200-2011 (CUB-200-2011) dataset is the most widely-used dataset for fine-grained visual categorization task.

Images Image Classification Image Generation Zero-Shot Learning Few-Shot Image Classification Image Retrieval Few-Shot Learning+29 tasks

2,235 papers · 47 benchmarks

UCF101 (UCF101 Human Actions dataset)

UCF101 dataset is an extension of UCF50 and consists of 13,320 video clips, which are classified into 101 categories.

Videos Zero-Shot Learning Action Recognition Temporal Action Localization Few-Shot Learning Image Clustering Skeleton Based Action Recognition+16 tasks

1,863 papers · 23 benchmarks

SST-2

The Stanford Sentiment Treebank is a corpus with fully labeled parse trees that allows for a complete analysis of the compositional effects of sentiment in language.

Classification Text Classification Sentiment Analysis Few-Shot Learning Explanation Fidelity Evaluation Chinese Sentiment Analysis

1,808 papers · 2 benchmarks

mini-Imagenet

mini-Imagenet is proposed by Matching Networks for One Shot Learning .

Few-Shot Image Classification Few-Shot Learning Continual Learning Cross-Domain Few-Shot Unsupervised Few-Shot Image Classification Few-Shot Class-Incremental Learning

1,345 papers · 21 benchmarks

Oxford 102 Flower (102 Category Flower Dataset)

Oxford 102 Flower is an image classification dataset consisting of 102 flower categories.

Images Image Classification Image Generation Zero-Shot Learning Few-Shot Image Classification Few-Shot Learning Continual Learning+10 tasks

1,307 papers · 16 benchmarks

DTD (Describable Textures Dataset)

The Describable Textures Dataset (DTD) contains 5640 texture images in the wild.

Images Image Classification Classification Zero-Shot Learning Few-Shot Learning Image Clustering Neural Architecture Search+3 tasks

870 papers · 8 benchmarks

Food-101

The Food-101 dataset consists of 101 food categories with 750 training and 250 test images per category, making a total of 101k images.

Images Image Classification Classification Zero-Shot Learning Few-Shot Learning Image Clustering Fine-Grained Image Classification+10 tasks

805 papers · 14 benchmarks

Stanford Cars

The Stanford Cars dataset consists of 196 classes of cars with a total of 16,185 images, taken from the rear.

Images Image Classification Image Generation Zero-Shot Learning Few-Shot Image Classification Few-Shot Learning Continual Learning+7 tasks

790 papers · 13 benchmarks

MRPC (Microsoft Research Paraphrase Corpus)

Microsoft Research Paraphrase Corpus (MRPC) is a corpus consists of 5,801 sentence pairs collected from newswire articles.

Texts Few-Shot Learning Natural Language Inference Semantic Textual Similarity Semantic Textual Similarity within Bi-Encoder

786 papers · 4 benchmarks

EuroSAT

Eurosat is a dataset and deep learning benchmark for land use and land cover classification.

Images Image Classification Classification Semantic Segmentation Zero-Shot Learning Few-Shot Learning Image Clustering+4 tasks

687 papers · 8 benchmarks

FGVC-Aircraft

FGVC-Aircraft contains 10,200 images of aircraft, with 100 images for each of 102 different aircraft model variants, most of which are airplanes.

Images Image Classification Zero-Shot Learning Few-Shot Learning Image Clustering Fine-Grained Image Classification Neural Architecture Search+5 tasks

520 papers · 12 benchmarks

PubMedQA

The task of PubMedQA is to answer research questions with yes/no/maybe (e.g.: Do preoperative statins reduce atrial fibrillation after coronary artery bypass grafting?) using the corresponding abstracts.

Texts Question Answering Named Entity Recognition (NER)Few-Shot Learning Language Modelling Retrieval

276 papers · 3 benchmarks

PASCAL-5i

PASCAL-5i is a dataset used to evaluate few-shot segmentation.

Images Semantic Segmentation Few-Shot Learning Few-Shot Semantic Segmentation

177 papers · 1 benchmark

FLEURS (Few-shot Learning Evaluation of Universal Representations of Speech)

We introduce FLEURS, the Few-shot Learning Evaluation of Universal Representations of Speech benchmark.

Texts Audio Speech Recognition Few-Shot Learning Automatic Speech Recognition Automatic Speech Recognition (ASR)Spoken language identification automatic-speech-translation+1 tasks

141 papers · 1 benchmark

Meta-Dataset

The Meta-Dataset benchmark is a large few-shot learning benchmark and consists of multiple datasets of different data distributions.

Images Image Classification Few-Shot Image Classification Meta-Learning Few-Shot Learning

128 papers · 2 benchmarks

SUN397

The Scene UNderstanding (SUN) database contains 899 categories and 130,519 images.

Images Image Classification Zero-Shot Learning Few-Shot Learning Image Clustering Fine-Grained Image Classification Transductive Zero-Shot Classification+3 tasks

52 papers · 8 benchmarks

MR (MR Movie Reviews)

MR Movie Reviews is a dataset for use in sentiment-analysis experiments.

Texts Text Classification Sentiment Analysis Few-Shot Learning

28 papers · 3 benchmarks

CaseHOLD (Case Holdings On Legal Decisions)

CaseHOLD (Case Holdings On Legal Decisions) is a law dataset comprised of over 53,000+ multiple choice questions to identify the relevant holding of a cited case.

Texts Question Answering Few-Shot Learning

27 papers · 2 benchmarks

Wiki-One

This dataset is a Wikipedia dump, split by relations to perform Few-Shot Knowledge Graph Completion.

Graphs Knowledge Graph Completion Few-Shot Learning

16 papers · 0 benchmarks

Paris-Lille-3D

The Paris-Lille-3D is a Benchmark on Point Cloud Classification.

Images Semantic Segmentation Few-Shot Learning 3D Semantic Segmentation LIDAR Semantic Segmentation

15 papers · 1 benchmark

MedConceptsQA

MedConceptsQA - Open Source Medical Concepts QA Benchmark The benchmark can be found here: https://huggingface.co/datasets/ofir408/MedConceptsQA

Texts Question Answering Zero-Shot Learning Few-Shot Learning Large Language Model Medical Diagnosis Medical Procedure

13 papers · 2 benchmarks

MedNLI (Medical Natural Language Inference)

The MedNLI dataset consists of the sentence pairs developed by Physicians from the Past Medical History section of MIMIC-III clinical notes annotated for Definitely True, Maybe True and Definitely False.

Texts Medical Few-Shot Learning Natural Language Inference

9 papers · 2 benchmarks

GINC (Generative IN-Context learning Dataset)

GINC (Generative In-Context learning Dataset) is a small-scale synthetic dataset for studying in-context learning.

Texts Few-Shot Learning Language Modelling

7 papers · 0 benchmarks

ORBIT

ORBIT is a real-world few-shot dataset and benchmark grounded in a real-world application of teachable object recognizers for people who are blind/low vision.

Images Videos Few-Shot Image Classification Few-Shot Learning

7 papers · 2 benchmarks

N-Digit MNIST

N-Digit MNIST is a multi-digit MNIST-like dataset.

Images Few-Shot Learning Metric Learning Video Alignment

5 papers · 0 benchmarks

ExVo2022 (ICML ExVo 2022 Workshop & Competition Data)

Baseline code for the three tracks of ExVo 2022 competition.

Speech Few-Shot Learning

4 papers · 0 benchmarks

F-SIOL-310 (Few-Shot Incremental Object Learning)

F-SIOL-310 is a robotic dataset and benchmark for Few-Shot Incremental Object Learning, which is used to test incremental learning capabilities for robotic vision from a few examples.

Images Few-Shot Learning

4 papers · 0 benchmarks

FIGR-8

The FIGR-8 database is a dataset containing 17,375 classes of 1,548,256 images representing pictograms, ideograms, icons, emoticons or object or conception depictions.

Images Image Generation Meta-Learning Few-Shot Learning

4 papers · 0 benchmarks

FewSOL (A Dataset for Few-Shot Object Learning in Robotic Environments)

The Few-Shot Object Learning (FewSOL) dataset can be used for object recognition with a few images per object.

Images Texts RGB-D 6D Pose Estimation Few-Shot Image Classification Few-Shot Learning Few-Shot Semantic Segmentation Object Recognition Image-to-Text Retrieval+4 tasks

4 papers · 0 benchmarks

N-Omniglot

N-Omniglot is a neuromorphic dataset for few-shot learning.

Images Few-Shot Learning

4 papers · 0 benchmarks

BigNews

Contains 3,689,229 English news articles on politics, gathered from 11 United States (US) media outlets covering a broad ideological spectrum.

Texts Few-Shot Learning Stance Detection

3 papers · 0 benchmarks

Bongard-OpenWorld

Bongard-OpenWorld is a new benchmark for evaluating real-world few-shot reasoning for machine vision.

Images Texts Few-Shot Learning Visual Reasoning

3 papers · 1 benchmark

DOGC

Intended to provide freely available data sets in various formats together with basic annotation to be useful for applications in computational linguistics, translation studies and cross-linguistic corpus studies.

Few-Shot Learning Word Sense Disambiguation

3 papers · 0 benchmarks

CareCall (CareCall for Seniors)

carecall is a Korean dialogue dataset for role-satisfying dialogue systems.

Texts Few-Shot Learning Dialogue Generation

2 papers · 0 benchmarks

Large COVID-19 CT scan slice dataset

"We built a large lung CT scan dataset for COVID-19 by curating data from 7 public datasets listed in the acknowledgements.

Images Classification Few-Shot Learning COVID-19 Diagnosis Computed Tomography (CT)

2 papers · 2 benchmarks

ToM-in-AMC

ToM-in-AMC is a novel NLP benchmark, Short for Theory-of-Mind meta-learning Assessment with Movie Characters.

Texts Meta-Learning Few-Shot Learning

2 papers · 0 benchmarks

BankNote-Net

Millions of people around the world have low or no vision.

Image Classification Few-Shot Learning Few-Shot Object Detection Contrastive Learning

1 paper · 0 benchmarks

FewGLUE_64_labeled (A new version of FewGLUE with 64 training examples)

Introduction The FewGLUE64labeled dataset is a new version of FewGLUE dataset.

Texts Few-Shot Learning Natural Language Understanding

1 paper · 0 benchmarks

ISEKAI

ISEKAI dataset’s images are generated by Midjourney’s text-to-image model using well-crafted instructions.

Images Few-Shot Learning

1 paper · 0 benchmarks

MeerKAT: Meerkat Kalahari Audio Transcripts

A large-scale reference dataset for bioacoustics.

Audio Classification Few-Shot Learning Audio Classification Audio Tagging

1 paper · 1 benchmark

Open MIC (Open Museum Identification Challenge)

Open MIC (Open Museum Identification Challenge) contains photos of exhibits captured in 10 distinct exhibition spaces of several museums which showcase paintings, timepieces, sculptures, glassware, relics, science exhibits, natural history…

Images Domain Adaptation Few-Shot Learning Object Recognition

1 paper · 0 benchmarks

Events classification - Biotech news

A dataset specifically tailored to the biotech news sector, aiming to transcend the limitations of existing benchmarks.

Texts Text Classification Zero-Shot Learning Few-Shot Learning Few-Shot Text Classification Zero-Shot Text Classification

0 papers · 0 benchmarks

Paper counts and descriptions are the archive's, frozen 2025-07-28; no citation counts, no stars, no trending. Sorting by "most cited" or "newest" was a live-site feature the archive does not carry.

Few-Shot Learning datasets

Filter 51 task tags shown of 3,717, by dataset count; the full filter by modality, task and language is on /datasets

Few-Shot Learning datasets 1–45 of 45