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Compositional Zero-Shot Learning datasets

archive 2025-07-28

6 datasets carry the task tag "Compositional Zero-Shot Learning" (the task itself: Compositional Zero-Shot Learning), ordered by the archive's paper count. Page 1 of 1: 6 shown of 6. 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

Compositional Zero-Shot Learning datasets 1–6 of 6

The MIT-States dataset has 245 object classes, 115 attribute classes and ∼53K images.
91 papers · 4 benchmarks
C-GQA (Compositional GQA)
We propose a split built on top of Stanford GQA dataset originally proposed for VQA and name it Compositional GQA (C-GQA) dataset (see supplementary for the details).
42 papers · 0 benchmarks
UT Zappos50K is a large shoe dataset consisting of 50,025 catalog images collected from Zappos.com.
32 papers · 2 benchmarks
ReaSCAN (ReaSCAN: Compositional Reasoning in Language Grounding)
ReaSCAN is a synthetic navigation task that requires models to reason about surroundings over syntactically difficult languages.
10 papers · 0 benchmarks
AO-CLEVr is a new synthetic-images dataset containing images of "easy" Attribute-Object categories, based on the CLEVr.
6 papers · 0 benchmarks
UT Zappos50K (UT-Zap50K) is a large shoe dataset consisting of 50,025 catalog images collected from Zappos.com.
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.