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Prompt Engineering datasets

archive 2025-07-28

16 datasets carry the task tag "Prompt Engineering" (the task itself: Prompt Engineering), ordered by the archive's paper count. Page 1 of 1: 16 shown of 16. 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.

Prompt Engineering datasets 1–16 of 16

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

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

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

Caltech-101

The Caltech101 dataset contains images from 101 object categories (e.g., “helicopter”, “elephant” and “chair” etc.) and a background category that contains the images not from the 101 object categories.

Images Zero-Shot Learning Semi-Supervised Image Classification Image Clustering Fine-Grained Image Classification Unsupervised Anomaly Detection Transductive Zero-Shot Classification+3 tasks

709 papers · 10 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

ImageNet-R (ImageNet-Rendition)

ImageNet-R(endition) contains art, cartoons, deviantart, graffiti, embroidery, graphics, origami, paintings, patterns, plastic objects, plush objects, sculptures, sketches, tattoos, toys, and video game renditions of ImageNet classes.

Images Unsupervised Domain Adaptation Domain Generalization Zero-Shot Transfer Image Classification Prompt Engineering Zero-Shot Composed Image Retrieval (ZS-CIR)Zero-shot Image Retrieval

481 papers · 5 benchmarks

ImageNet-A

The ImageNet-A dataset consists of real-world, unmodified, and naturally occurring examples that are misclassified by ResNet models.

Images Unsupervised Domain Adaptation Domain Generalization Zero-Shot Transfer Image Classification Prompt Engineering Adversarial Robustness

431 papers · 5 benchmarks

Oxford-IIIT Pet Dataset

The Oxford-IIIT Pet Dataset has 37 categories with roughly 200 images for each class.

Images Image Classification Fine-Grained Image Classification Neural Architecture Search Prompt Engineering Image Compression

90 papers · 5 benchmarks

Oxford-IIIT Pets

The Oxford-IIIT Pet Dataset is a 37-category pet dataset with roughly 200 images for each class.

Image Classification Zero-Shot Learning Image Clustering Fine-Grained Image Classification Neural Architecture Search Transductive Zero-Shot Classification+2 tasks

59 papers · 5 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

ImageNet-S (ImageNet Semantic Segmentation)

Powered by the ImageNet dataset, unsupervised learning on large-scale data has made significant advances for classification tasks.

Images Semantic Segmentation Semi-Supervised Semantic Segmentation Unsupervised Semantic Segmentation Zero-Shot Transfer Image Classification Prompt Engineering

43 papers · 6 benchmarks

OmniBenchmark

Omni-Realm Benchmark (OmniBenchmark) is a diverse (21 semantic realm-wise datasets) and concise (realm-wise datasets have no concepts overlapping) benchmark for evaluating pre-trained model generalization across semantic…

Images Image Classification Representation Learning Prompt Engineering Fine-Grained Image Recognition

29 papers · 1 benchmark

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.

Prompt Engineering datasets

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

Prompt Engineering datasets 1–16 of 16