{"id":"https://openalex.org/W2738321088","doi":"https://doi.org/10.18653/v1/d17-1030","title":"High-risk learning: acquiring new word vectors from tiny data","display_name":"High-risk learning: acquiring new word vectors from tiny data","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2738321088","doi":"https://doi.org/10.18653/v1/d17-1030","mag":"2738321088"},"language":"en","primary_location":{"id":"doi:10.18653/v1/d17-1030","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d17-1030","pdf_url":"https://www.aclweb.org/anthology/D17-1030.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2017 Conference on Empirical Methods in Natural\n          Language Processing","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/D17-1030.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5036912765","display_name":"Aur\u00e9lie Herbelot","orcid":"https://orcid.org/0000-0002-4353-5908"},"institutions":[{"id":"https://openalex.org/I193223587","display_name":"University of Trento","ror":"https://ror.org/05trd4x28","country_code":"IT","type":"education","lineage":["https://openalex.org/I193223587"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Aur\u00e9lie Herbelot","raw_affiliation_strings":["Dept. of Translation and Language Sciences Universitat Pompeu Fabra","University of Trento, Trento, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Translation and Language Sciences Universitat Pompeu Fabra","institution_ids":[]},{"raw_affiliation_string":"University of Trento, Trento, Italy","institution_ids":["https://openalex.org/I193223587"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038612405","display_name":"Marco Baroni","orcid":"https://orcid.org/0000-0001-5066-3580"},"institutions":[{"id":"https://openalex.org/I193223587","display_name":"University of Trento","ror":"https://ror.org/05trd4x28","country_code":"IT","type":"education","lineage":["https://openalex.org/I193223587"]},{"id":"https://openalex.org/I2252078561","display_name":"Meta (Israel)","ror":"https://ror.org/02388em19","country_code":"IL","type":"company","lineage":["https://openalex.org/I2252078561","https://openalex.org/I4210114444"]}],"countries":["IL","IT"],"is_corresponding":false,"raw_author_name":"Marco Baroni","raw_affiliation_strings":["Center for Mind/Brain Sciences University of Trento","Meta (Israel), Tel Aviv, Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Mind/Brain Sciences University of Trento","institution_ids":["https://openalex.org/I193223587"]},{"raw_affiliation_string":"Meta (Israel), Tel Aviv, Israel","institution_ids":["https://openalex.org/I2252078561"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.8587,"has_fulltext":true,"cited_by_count":15,"citation_normalized_percentile":{"value":0.89209094,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"304","last_page":"309"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9940999746322632,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7470380663871765},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.738516092300415},{"id":"https://openalex.org/keywords/word2vec","display_name":"Word2vec","score":0.6970656514167786},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6650416254997253},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6631369590759277},{"id":"https://openalex.org/keywords/cryptographic-nonce","display_name":"Cryptographic nonce","score":0.5923962593078613},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5727022290229797},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5656096935272217},{"id":"https://openalex.org/keywords/meaning","display_name":"Meaning (existential)","score":0.5179440379142761},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.5064324140548706},{"id":"https://openalex.org/keywords/distributional-semantics","display_name":"Distributional semantics","score":0.45160895586013794},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.2276436686515808},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.1746877133846283},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.07815080881118774}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7470380663871765},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.738516092300415},{"id":"https://openalex.org/C2776461190","wikidata":"https://www.wikidata.org/wiki/Q22673982","display_name":"Word2vec","level":3,"score":0.6970656514167786},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6650416254997253},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6631369590759277},{"id":"https://openalex.org/C9996903","wikidata":"https://www.wikidata.org/wiki/Q1749235","display_name":"Cryptographic nonce","level":3,"score":0.5923962593078613},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5727022290229797},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5656096935272217},{"id":"https://openalex.org/C2780876879","wikidata":"https://www.wikidata.org/wiki/Q3054749","display_name":"Meaning (existential)","level":2,"score":0.5179440379142761},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.5064324140548706},{"id":"https://openalex.org/C2778828372","wikidata":"https://www.wikidata.org/wiki/Q5283209","display_name":"Distributional semantics","level":3,"score":0.45160895586013794},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.2276436686515808},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.1746877133846283},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.07815080881118774},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C148730421","wikidata":"https://www.wikidata.org/wiki/Q141090","display_name":"Encryption","level":2,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.18653/v1/d17-1030","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d17-1030","pdf_url":"https://www.aclweb.org/anthology/D17-1030.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2017 Conference on Empirical Methods in Natural\n          Language Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:repositori-api.upf.edu:10230/45966","is_oa":true,"landing_page_url":"http://hdl.handle.net/10230/45966","pdf_url":null,"source":{"id":"https://openalex.org/S4306402615","display_name":"Repositori digital de la UPF (Universitat Pompeu Fabra)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I170486558","host_organization_name":"Universitat Pompeu Fabra","host_organization_lineage":["https://openalex.org/I170486558"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:arXiv.org:1707.06556","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1707.06556","pdf_url":"https://arxiv.org/pdf/1707.06556","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"pmh:oai:iris.unitn.it:11572/196359","is_oa":true,"landing_page_url":"http://hdl.handle.net/11572/196359","pdf_url":"https://iris.unitn.it/bitstream/11572/196359/5/D17-1030.pdf","source":{"id":"https://openalex.org/S4306401913","display_name":"Institutional Research Information System (Universit\u00e0 degli Studi di Trento)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I193223587","host_organization_name":"University of Trento","host_organization_lineage":["https://openalex.org/I193223587"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"mag:2738321088","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1707.06556.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1707.06556","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1707.06556","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.18653/v1/d17-1030","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d17-1030","pdf_url":"https://www.aclweb.org/anthology/D17-1030.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2017 Conference on Empirical Methods in Natural\n          Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.8299999833106995,"display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G1795524866","display_name":"A Theory of Reference for Distributional Semantics","funder_award_id":"751250","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G2275620189","display_name":"Compositional Operations in Semantic Space","funder_award_id":"283554","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G7842005466","display_name":null,"funder_award_id":"Horizon 2020","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2738321088.pdf","grobid_xml":"https://content.openalex.org/works/W2738321088.grobid-xml"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W1597195725","https://openalex.org/W1662133657","https://openalex.org/W1958547877","https://openalex.org/W2041945486","https://openalex.org/W2112184938","https://openalex.org/W2132339004","https://openalex.org/W2155870214","https://openalex.org/W2164019165","https://openalex.org/W2167419393","https://openalex.org/W2251012068","https://openalex.org/W2251966070","https://openalex.org/W2325858707","https://openalex.org/W2401823607","https://openalex.org/W2601529995","https://openalex.org/W2950133940","https://openalex.org/W2952230511","https://openalex.org/W2963305465","https://openalex.org/W3098682828"],"related_works":["https://openalex.org/W2963956670","https://openalex.org/W2737092125","https://openalex.org/W2735548109","https://openalex.org/W2250539671","https://openalex.org/W2978411033","https://openalex.org/W3172797824","https://openalex.org/W2889940099","https://openalex.org/W2949201587","https://openalex.org/W2551572025","https://openalex.org/W2164019165","https://openalex.org/W2981499762","https://openalex.org/W2953405964","https://openalex.org/W2890560993","https://openalex.org/W3104806203","https://openalex.org/W2724653607","https://openalex.org/W2407950365","https://openalex.org/W1937075317","https://openalex.org/W2950577311","https://openalex.org/W2806906294","https://openalex.org/W3122121542"],"abstract_inverted_index":{"Distributional":[0],"semantics":[1],"models":[2,115],"are":[3],"known":[4],"to":[5,17,69,73],"struggle":[6],"with":[7],"small":[8],"data.":[9],"It":[10],"is":[11],"generally":[12],"accepted":[13],"that":[14,38,57],"in":[15,111],"order":[16],"learn":[18,74],"'a":[19],"good":[20],"vector'":[21],"for":[22],"a":[23,25,45,48,58,84,98,108],"word,":[24],"model":[26,61,92],"must":[27],"have":[28],"sufficient":[29],"examples":[30],"of":[31,44,105],"its":[32,70],"usage.":[33],"This":[34],"contradicts":[35],"the":[36,42,117],"fact":[37],"humans":[39],"can":[40],"guess":[41],"meaning":[43],"word":[46,94],"from":[47,77,83],"few":[49],"occurrences":[50],"only.":[51],"In":[52],"this":[53],"paper,":[54],"we":[55],"show":[56],"neural":[59],"language":[60],"such":[62],"as":[63],"Word2Vec":[64],"only":[65],"necessitates":[66],"minor":[67],"modifications":[68],"standard":[71],"architecture":[72],"new":[75],"terms":[76],"tiny":[78],"data,":[79],"using":[80],"background":[81],"knowledge":[82],"previously":[85],"learnt":[86],"semantic":[87],"space.":[88],"We":[89],"test":[90],"our":[91],"on":[93,97,116],"definitions":[95],"and":[96],"nonce":[99],"task":[100],"involving":[101],"2-6":[102],"sentences'":[103],"worth":[104],"context,":[106],"showing":[107],"large":[109],"increase":[110],"performance":[112],"over":[113],"state-of-the-art":[114],"definitional":[118],"task.":[119]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1}],"updated_date":"2026-06-16T09:24:06.705377","created_date":"2025-10-10T00:00:00"}
