MTEB is a benchmark that spans 8 embedding tasks covering a total of 56 datasets and 112 languages. The 8 task types are Bitext mining, Classification, Clustering, Pair Classification, Reranking, Retrieval, Semantic Textual Similarity and Summarisation. The 56 datasets contain varying text lengths and they are grouped into three categories: Sentence to sentence, Paragraph to paragraph, and Sentence to paragraph.
54 PAPERS • 8 BENCHMARKS
A dataset of games played in the card game "Cards Against Humanity" (CAH), by human players, derived from the online CAH labs. Each round includes the cards presented to users - a "black" prompt with a blank or question and 10 "white" punchlines as possible responses, and which punchline was picked by a player each round, along with text and metadata.
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The Multi-Eup is a new multilingual benchmark dataset, comprising 22K multilingual documents collected from the European Parliament, spanning 24 languages. This dataset is designed to investigate fairness in a multilingual information retrieval (IR) context to analyze both language and demographic bias in a ranking context. It boasts an authentic multilingual corpus, featuring topics translated into all 24 languages, as well as cross-lingual relevance judgments. Furthermore, it offers rich demographic information associated with its documents, facilitating the study of demographic bias.
1 PAPER • 1 BENCHMARK