{ "AILAStatutes-query": "Identifying the most relevant statutes for a given situation", "AfriSentiClassification": "Given a text, categorized by sentiment into positive, negative, or neutral", "AlloProfClusteringS2S.v2": "Identify the topic of document titles from Allo Prof dataset", "AlloprofReranking-query": "Given a question, retrieve passages that answer the question", "AmazonCounterfactualClassification": "Given an Amazon review, judge whether it is counterfactual.", "ArXivHierarchicalClusteringP2P": "Identify the main and secondary category of Arxiv papers based on the titles and abstracts", "ArXivHierarchicalClusteringS2S": "Identify the main and secondary category of Arxiv papers based on the titles", "ArguAna-query": "Given a claim, find documents that refute the claim", "ArmenianParaphrasePC": "Retrieve semantically similar text", "BUCC.v2": "Retrieve parallel sentences", "BelebeleRetrieval-query": "Retrieval the relevant passage for the given query", "BibleNLPBitextMining": "Retrieve parallel sentences", "BigPatentClustering.v2": "Identify the category of documents from the Big Patent dataset", "BiorxivClusteringP2P.v2": "Identify the main category of Biorxiv papers based on the titles and abstracts", "BornholmBitextMining": "Retrieve parallel sentences", "BrazilianToxicTweetsClassification": "Classify the toxic tweets in Brazilian Portuguese into one of the six categories: LGBTQ+phobia, Xenophobia, Obscene, Insult, Misogyny and Racism.", "BulgarianStoreReviewSentimentClassfication": "Classify user reviews into positive, negative or mixed sentiment", "CEDRClassification": "Given a comment as query, classify expressed emotions into joy, sadness, surprise, fear, and anger", "CLSClusteringP2P.v2": "Identify the main category of scholar papers based on the titles and abstracts", "CSFDSKMovieReviewSentimentClassification": "Given a movie review, classify its rating on a scale from 0 to 5", "CTKFactsNLI": "Retrieve semantically similar text", "CataloniaTweetClassification": "Given a tweet, classify its sentiment into AGAINST, FAVOR or NEUTRAL towards Catalonia's independence.", "Core17InstructionRetrieval-query": "Retrieve relevant passages for the given query with conditions", "CovidRetrieval-query": "Given a question on COVID-19, retrieve news articles that answer the question", "CyrillicTurkicLangClassification": "Given a text, classify its language", "CzechProductReviewSentimentClassification": "Classify product reviews into positive, neutral, or negative sentiment", "DBpediaClassification": "Given the following text, retrieve the appropriate DBpedia category including Company, EducationalInstitution, Artist, Athlete, OfficeHolder, MeanOfTransportation, Building, NaturalPlace, Village, Animal, Plant, Album, Film, WrittenWork.", "DalajClassification": "Classify texts based on linguistic acceptability in Swedish", "DiaBlaBitextMining": "Retrieve parallel sentences", "EstonianValenceClassification": "Given a news article, categorized by sentiment into negatiivne, positiivne, neutraalne or vastuolulin", "FaroeseSTS": "Retrieve semantically similar text", "FilipinoShopeeReviewsClassification": "Given a shop review, classify its rating on a scale from 1 to 5", "FinParaSTS": "Retrieve semantically similar text", "FinancialPhrasebankClassification": "Given financial news, categorized by sentiment into positive, negative, or neutral", "FloresBitextMining": "Retrieve parallel sentences", "GermanSTSBenchmark": "Retrieve semantically similar text", "GreekLegalCodeClassification": "Given a greek legal text, classify its topic", "GujaratiNewsClassification": "Given a Gujarati news articles, classify ist topic", "HALClusteringS2S.v2": "Identify the topic of titles from HAL", "HagridRetrieval-query": "Given a question, retrieve relevant responses", "IN22GenBitextMining": "Retrieve parallel sentences", "IndicCrosslingualSTS": "Retrieve semantically similar text", "IndicGenBenchFloresBitextMining": "Retrieve parallel sentences", "IndicLangClassification": "Given a text, classify its language", "IndonesianIdClickbaitClassification": "Given an Indonesian news headlines, classify its into clickbait or non-clickbait", "IsiZuluNewsClassification": "Given a news article, classify its topic", "ItaCaseholdClassification": "Given a judgments, classify its topic", "JSICK": "Retrieve semantically similar text", "KorHateSpeechMLClassification": "Given a Korean online news comments, classify its fine-grained hate speech classes", "KorSarcasmClassification": "Given a twitter, categorized it into sarcasm or not_sarcasm", "KurdishSentimentClassification": "Given a text, categorized by sentiment into positive or negative", "LEMBPasskeyRetrieval-query": "Retrieval the relevant passage for the given query", "LegalBenchCorporateLobbying-query": "Given a query, retrieve relevant legal bill summaries", "MIRACLRetrievalHardNegatives-query": "Retrieve Wikipedia passages that answer the question", "MLQARetrieval-query": "Retrieval the relevant passage for the given query", "MacedonianTweetSentimentClassification": "Given a Macedonian tweet, categorized by sentiment into positive, negative, or neutral", "MalteseNewsClassification": "Given a maltese new, classify its topic", "MasakhaNEWSClassification": "Classify the News in the given texts into one of the seven category: politics,sports,health,business,entertainment,technology,religion ", "MasakhaNEWSClusteringS2S": "Identify the topic or theme of the given news articles based on the titles", "MassiveIntentClassification": "Given a user utterance as query, find the user intents", "MedrxivClusteringP2P.v2": "Identify the main category of Medrxiv papers based on the titles and abstracts", "MultiEURLEXMultilabelClassification": "Given a text, classify its topic", "MultiHateClassification": "Given a text, categorized by sentiment into hate or non-hate", "NTREXBitextMining": "Retrieve parallel sentences", "NepaliNewsClassification": "Given a news article, categorized it into business, entertainment or sports", "News21InstructionRetrieval-query": "Retrieve relevant passages for the given query with conditions", "NollySentiBitextMining": "Retrieve parallel sentences", "NordicLangClassification": "Given a text in a Nordic language, classify the language into one of the following categories: Danish, Swedish, Norwegian (Nynorsk), Norwegian (Bokmål), Faroese, Icelandic.", "NorwegianCourtsBitextMining": "Retrieve parallel sentences", "NusaParagraphEmotionClassification": "Classify the emotion into one of the following categories: fear, sadness, anger, happy, love, surprise, shame.", "NusaTranslationBitextMining": "Retrieve parallel sentences", "NusaX-senti": "Given a text, categorized by sentiment into positive or negative", "NusaXBitextMining": "Retrieve parallel sentences", "OdiaNewsClassification": "Given a news article, categorized it into business, entertainment or sports", "OpusparcusPC": "Retrieve semantically similar text", "PAC": "Classify Polish contract clauses into one of the following two types: \"Safe Contract Clauses\" and \"Unfair Contract Clauses\".", "PawsXPairClassification": "Retrieve semantically similar text", "PlscClusteringP2P.v2": "Identify the category of titles+abstracts from Library of Science", "PoemSentimentClassification": "Given the following verse from a poem, classify its sentiment as negative, neutral, positive, or mixed.", "PolEmo2.0-OUT": "Classify the sentiment of products and school online reviews", "PpcPC": "Retrieve semantically similar text", "PunjabiNewsClassification": "Given a news article, categorized it into two-classes", "RTE3": "Retrieve semantically similar text", "Robust04InstructionRetrieval-query": "Retrieve relevant passages for the given query with conditions", "RomaniBibleClustering": "Identify verses from the Bible in Kalderash Romani by book.", "RuBQReranking-query": "Given a question, retrieve Wikipedia passages that answer the question", "SCIDOCS-query": "Given a scientific paper title, retrieve paper abstracts that are cited by the given paper", "SIB200ClusteringS2S": "Identify the category of documents", "SICK-R": "Retrieve semantically similar text", "STS12": "Retrieve semantically related sentences", "STS13": "Retrieve semantically similar text", "STS14": "Retrieve semantically similar text", "STS15": "Retrieve semantically similar text", "STS17": "Retrieve semantically similar text", "STS22.v2": "Given a document, retrieve semantically related documents", "STSB": "Retrieve semantically similar text", "STSBenchmark": "Retrieve semantically similar text", "STSES": "Given a Spanish sentence, retrieve semantically related Spanish sentences", "ScalaClassification": "Classify passages into correct or correct in Scandinavian Languages based on linguistic acceptability", "SemRel24STS": "Retrieve semantically similar text", "SentimentAnalysisHindi": "Given a hindi text, categorized by sentiment into positive, negative or neutral", "SinhalaNewsClassification": "Given a news article, categorized it into political, business, technology, sports and Entertainment", "SiswatiNewsClassification": "Identify fine-grained news categories in Siswati language.", "SlovakMovieReviewSentimentClassification": "Given a movie review, categorized it into positive or negative", "SpartQA-query": "Given the following spatial reasoning question, retrieve the right answer.", "SprintDuplicateQuestions": "Find questions that have the same meaning as the input question", "StackExchangeClustering.v2": "Identify the topic or theme of StackExchange posts based on the titles", "StackOverflowQA-query": "Given a question about coding, retrieval code or passage that can solve user's question", "StatcanDialogueDatasetRetrieval-query": "Retrieval the relevant passage for the given query", "SwahiliNewsClassification": "Given a news article, classify its domain", "SwednClusteringP2P": "Identify news categories in Swedish passages", "SwissJudgementClassification": "Given a news article, categorized it into approval or dismissal", "T2Reranking-query": "Given a Chinese search query, retrieve web passages that answer the question", "TERRa": "Given a premise, retrieve a hypothesis that is entailed by the premise", "TRECCOVID-query": "Given a medical query, retrieve documents that answer the query", "Tatoeba": "Retrieve parallel sentences", "TempReasonL1-query": "Given the following question about time, retrieve the correct answer.", "ToxicConversationsClassification": "Classify the given comments as either toxic or not toxic", "TswanaNewsClassification": "Given a news article, classify its topic", "TweetTopicSingleClassification": "Gvien a twitter, classify its topic", "TwitterHjerneRetrieval-query": "Retrieve answers to questions asked in Danish tweets", "TwitterURLCorpus": "Find tweets that have the same meaning as the input tweet", "VoyageMMarcoReranking-query": "Given a Japanese search query, retrieve web passages that answer the question", "WebLINXCandidatesReranking-query": "Retrieval the relevant passage for the given query", "WikiCitiesClustering": "Identify of Wikipedia articles of cities by country", "WikiClusteringP2P.v2": "Identify the category of wiki passages", "WikipediaRerankingMultilingual-query": "Retrieval the relevant passage for the given query", "WikipediaRetrievalMultilingual-query": "Retrieval the relevant passage for the given query", "WinoGrande-query": "Given the following sentence, retrieve an appropriate answer to fill in the missing underscored part.", "XNLI": "Retrieve semantically similar text", "indonli": "Retrieve semantically similar text" }