{"url":"/dataset/unified-ssl-benchmark-usb","name":"Unified SSL Benchmark (USB)","full_name":null,"description_markdown":"The Unified SSL Benchmark (USB) consists of 15 diverse, challenging, and comprehensive tasks from CV, natural language processing (NLP), and audio processing (Audio) to evaluate self-supervised learning (SSL) methods. A modular and extensible codebase is open-sourced for fair evaluation on these SSL methods.","description_withheld":null,"homepage":"https://github.com/microsoft/semi-supervised-learning","introduced_date":"2022-08-12","introduced_date_note":null,"introduced_by":{"paper":"/paper/usb-a-unified-semi-supervised-learning","title":"USB: A Unified Semi-supervised Learning Benchmark for Classification","first_author":"Yidong Wang","url":null},"license":{"name":"MIT License","url":"https://github.com/microsoft/Semi-supervised-learning/blob/main/LICENSE.txt"},"modalities":[],"tasks":[{"name":"Self-Supervised Learning","url":"/task/self-supervised-learning","datasets_with_task":"/datasets/task/self-supervised-learning"}],"languages":[],"variants":["Unified SSL Benchmark (USB)"],"data_loaders":[],"num_papers_in_archive":2,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-25T09:33:49+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}