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Learning-To-Rank datasets

archive 2025-07-28

9 datasets carry the task tag "Learning-To-Rank" (the task itself: Learning-To-Rank), ordered by the archive's paper count. Page 1 of 1: 9 shown of 9. 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.

Learning-To-Rank datasets 1–9 of 9

MSLR-WEB10K

The MSLR-WEB10K dataset consists of 10,000 search queries over the documents from search results.

Ranking Question Answering Information Retrieval Learning-To-Rank

36 papers · 0 benchmarks

MQ2007

The MQ2007 dataset consists of queries, corresponding retrieved documents and labels provided by human experts.

Ranking Meta-Learning Information Retrieval Learning-To-Rank

32 papers · 0 benchmarks

MQ2008

The MQ2008 dataset is a dataset for Learning to Rank.

Texts Ranking Information Retrieval Document Ranking Learning-To-Rank

31 papers · 0 benchmarks

Learning to Rank Challenge (Yahoo! Learning to Rank Challenge)

The Yahoo!

Texts Tabular Recommendation Systems Information Retrieval Learning-To-Rank

25 papers · 0 benchmarks

MultiFC

Publicly available dataset of naturally occurring factual claims for the purpose of automatic claim verification.

Texts Semantic Textual Similarity Semantic Similarity Learning-To-Rank

21 papers · 0 benchmarks

ReQA (Retrieval Question-Answering)

Retrieval Question-Answering (ReQA) benchmark tests a model’s ability to retrieve relevant answers efficiently from a large set of documents.

Texts Question Answering Information Retrieval Learning-To-Rank

10 papers · 0 benchmarks

ART Dataset (Abductive Reasoning in narrative Text)

ART consists of over 20k commonsense narrative contexts and 200k explanations.

Texts Language Modelling Natural Language Inference Learning-To-Rank

9 papers · 0 benchmarks

Flickr Cropping Dataset

The Flick Cropping Dataset consists of high quality cropping and pairwise ranking annotations used to evaluate the performance of automatic image cropping approaches.

Images Decision Making Image Cropping Learning-To-Rank

5 papers · 0 benchmarks

REFreSD (Rationalized English-French Semantic Divergences)

Consists of English-French sentence-pairs annotated with semantic divergence classes and token-level rationales.

Learning-To-Rank

3 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.

Learning-To-Rank datasets

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

Learning-To-Rank datasets 1–9 of 9