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Few-Shot Text Classification datasets

archive 2025-07-28

4 datasets carry the task tag "Few-Shot Text Classification" (the task itself: Few-Shot Text Classification), 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

Few-Shot Text Classification datasets 1–4 of 4

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.
2,354 papers · 6 benchmarks
The SST-5, also known as the Stanford Sentiment Treebank with 5 labels, is a dataset used for sentiment analysis.
338 papers · 2 benchmarks
RAFT (Realworld Annotated Few-shot Tasks)
The RAFT benchmark (Realworld Annotated Few-shot Tasks) focuses on naturally occurring tasks and uses an evaluation setup that mirrors deployment.
18 papers · 1 benchmark
A dataset specifically tailored to the biotech news sector, aiming to transcend the limitations of existing benchmarks.
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.