</> Code with Papers by Syntology

Home › Datasets › task › Open-World Semi-Supervised Learning

Open-World Semi-Supervised Learning datasets

archive 2025-07-28

4 datasets carry the task tag "Open-World Semi-Supervised Learning" (the task itself: Open-World Semi-Supervised Learning), ordered by the archive's paper count. Page 1 of 1: 4 shown of 4. 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.

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

All 12,172 Question Answering 413Semantic Segmentation 347Object Detection 332Image Classification 283Classification 222Text Classification 167Language Modelling 166Text Generation 162Visual Question Answering (VQA) 144Named Entity Recognition (NER) 130Pose Estimation 124Anomaly Detection 119Action Recognition 115Instance Segmentation 111Sentiment Analysis 104Text Summarization 98Domain Adaptation 96Speech Recognition 96Reading Comprehension 95Information Retrieval 932D Object Detection 92Image Retrieval 87Machine Translation 82Relation Extraction 822D Semantic Segmentation 81Natural Language Inference 81Image Captioning 79Image Generation 79Depth Estimation 77Node Classification 75Natural Language Understanding 72Autonomous Driving 70Code Generation 70Object Tracking 693D Object Detection 67Face Recognition 67Link Prediction 67Person Re-Identification 65Data Augmentation 63Multi-Task Learning 593D Reconstruction 58Common Sense Reasoning 56Recommendation Systems 56Video Understanding 56Optical Character Recognition (OCR) 55Graph Classification 54Abstractive Text Summarization 52Emotion Recognition 52Medical Image Segmentation 52Word Embeddings 52Open-World Semi-Supervised Learning 4

Open-World Semi-Supervised Learning datasets 1–4 of 4

CIFAR-10
description withheld: archive row vandalised before snapshot
ImagesImage ClassificationClassificationImage GenerationZero-Shot LearningAnomaly DetectionImage Retrieval+58 tasks
16,145 papers · 91 benchmarks
CIFAR-100
The CIFAR-100 dataset (Canadian Institute for Advanced Research, 100 classes) is a subset of the Tiny Images dataset and consists of 60000 32x32 color images.
ImagesImage ClassificationClassificationImage GenerationZero-Shot LearningAnomaly DetectionFew-Shot Image Classification+37 tasks
9,045 papers · 51 benchmarks
ImageNet-100 (TEMI Split)
This split was introduced in TEMI (BMVC 2023) Adaloglou, Nikolas, Felix Michels, Hamza Kalisch, and Markus Kollmann.
Image ClassificationImage ClusteringSelf-Supervised LearningOpen-World Semi-Supervised Learning
12 papers · 4 benchmarks
BIOSCAN-5M
As part of an ongoing worldwide effort to comprehend and monitor insect biodiversity, we present the BIOSCAN-5M Insect dataset to the machine learning community.
ImagesBiologyClassificationSemi-Supervised Image ClassificationDomain GeneralizationTransfer LearningHierarchical Multi-label ClassificationMultimodal Deep Learning+4 tasks
4 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.