{"id":"https://openalex.org/W2948588982","doi":"https://doi.org/10.18653/v1/p19-1385","title":"Attention-based Conditioning Methods for External Knowledge Integration","display_name":"Attention-based Conditioning Methods for External Knowledge Integration","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2948588982","doi":"https://doi.org/10.18653/v1/p19-1385","mag":"2948588982"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p19-1385","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1385","pdf_url":"https://www.aclweb.org/anthology/P19-1385.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 57th Annual Meeting of the Association for Computational Linguistics","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/P19-1385.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054791689","display_name":"Katerina Margatina","orcid":null},"institutions":[{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Katerina Margatina","raw_affiliation_strings":["School of ECE, National Technical University of Athens, Athens, Greece","National Technical Univ. of Athens#TAB#"],"affiliations":[{"raw_affiliation_string":"School of ECE, National Technical University of Athens, Athens, Greece","institution_ids":["https://openalex.org/I174458059"]},{"raw_affiliation_string":"National Technical Univ. of Athens#TAB#","institution_ids":["https://openalex.org/I174458059"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035665045","display_name":"Christos Baziotis","orcid":null},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Christos Baziotis","raw_affiliation_strings":["School of Informatics, University of Edinburgh, UK","University of Edinburgh,"],"affiliations":[{"raw_affiliation_string":"School of Informatics, University of Edinburgh, UK","institution_ids":["https://openalex.org/I98677209"]},{"raw_affiliation_string":"University of Edinburgh,","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084949286","display_name":"Alexandros Potamianos","orcid":"https://orcid.org/0009-0007-1532-5288"},"institutions":[{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Alexandros Potamianos","raw_affiliation_strings":["National Technical Univ. of Athens#TAB#"],"affiliations":[{"raw_affiliation_string":"National Technical Univ. of Athens#TAB#","institution_ids":["https://openalex.org/I174458059"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5054791689"],"corresponding_institution_ids":["https://openalex.org/I174458059"],"apc_list":null,"apc_paid":null,"fwci":0.4335,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.71246858,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"3944","last_page":"3951"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9995999932289124,"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":0.9995999932289124,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9993000030517578,"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":0.9993000030517578,"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":0.7864814400672913},{"id":"https://openalex.org/keywords/concatenation","display_name":"Concatenation (mathematics)","score":0.7048559784889221},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.647626519203186},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6463054418563843},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.5911501049995422},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5625085830688477},{"id":"https://openalex.org/keywords/gating","display_name":"Gating","score":0.5425589084625244},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4991168975830078},{"id":"https://openalex.org/keywords/affine-transformation","display_name":"Affine transformation","score":0.4892404079437256},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41499167680740356},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.34081679582595825},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06521958112716675}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7864814400672913},{"id":"https://openalex.org/C87619178","wikidata":"https://www.wikidata.org/wiki/Q126002","display_name":"Concatenation (mathematics)","level":2,"score":0.7048559784889221},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.647626519203186},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6463054418563843},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.5911501049995422},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5625085830688477},{"id":"https://openalex.org/C194544171","wikidata":"https://www.wikidata.org/wiki/Q21105679","display_name":"Gating","level":2,"score":0.5425589084625244},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4991168975830078},{"id":"https://openalex.org/C92757383","wikidata":"https://www.wikidata.org/wiki/Q382497","display_name":"Affine transformation","level":2,"score":0.4892404079437256},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41499167680740356},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.34081679582595825},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06521958112716675},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C42407357","wikidata":"https://www.wikidata.org/wiki/Q521","display_name":"Physiology","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.18653/v1/p19-1385","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1385","pdf_url":"https://www.aclweb.org/anthology/P19-1385.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 57th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1906.03674","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1906.03674","pdf_url":"https://arxiv.org/pdf/1906.03674","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":"mag:2948588982","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1906.03674.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.1906.03674","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1906.03674","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/p19-1385","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1385","pdf_url":"https://www.aclweb.org/anthology/P19-1385.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 57th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4447653093","display_name":null,"funder_award_id":"Network","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G4956428346","display_name":null,"funder_award_id":"Horizon 2020 research and innovatio","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G5036817778","display_name":null,"funder_award_id":"European Union's Horizon 2020 research and innov","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G6458387989","display_name":"Global Under-Resourced MEedia Translation","funder_award_id":"825299","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G8318064016","display_name":null,"funder_award_id":"Horizon","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G8633428685","display_name":null,"funder_award_id":"European Union's Horizon 2020 research and innovat","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"}],"funders":[{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"},{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2948588982.pdf","grobid_xml":"https://content.openalex.org/works/W2948588982.grobid-xml"},"referenced_works_count":56,"referenced_works":["https://openalex.org/W1514535095","https://openalex.org/W1522301498","https://openalex.org/W1815076433","https://openalex.org/W1964613733","https://openalex.org/W1988733743","https://openalex.org/W2017238344","https://openalex.org/W2064675550","https://openalex.org/W2084046180","https://openalex.org/W2112422413","https://openalex.org/W2118463056","https://openalex.org/W2140910804","https://openalex.org/W2153579005","https://openalex.org/W2156413587","https://openalex.org/W2160660844","https://openalex.org/W2250539671","https://openalex.org/W2250930514","https://openalex.org/W2251939518","https://openalex.org/W2267186426","https://openalex.org/W2476140796","https://openalex.org/W2493916176","https://openalex.org/W2525778437","https://openalex.org/W2545656684","https://openalex.org/W2567406479","https://openalex.org/W2578781754","https://openalex.org/W2620558438","https://openalex.org/W2750747353","https://openalex.org/W2807333695","https://openalex.org/W2879390606","https://openalex.org/W2886247548","https://openalex.org/W2891417293","https://openalex.org/W2898936689","https://openalex.org/W2899771611","https://openalex.org/W2916132663","https://openalex.org/W2950426098","https://openalex.org/W2962739339","https://openalex.org/W2962809001","https://openalex.org/W2962824509","https://openalex.org/W2962958286","https://openalex.org/W2962974772","https://openalex.org/W2963119602","https://openalex.org/W2963280802","https://openalex.org/W2963386218","https://openalex.org/W2963403868","https://openalex.org/W2963563735","https://openalex.org/W2963619022","https://openalex.org/W2963756346","https://openalex.org/W2963871484","https://openalex.org/W2963921132","https://openalex.org/W2963942654","https://openalex.org/W2963970792","https://openalex.org/W2964022793","https://openalex.org/W2964101952","https://openalex.org/W2964189376","https://openalex.org/W2964308564","https://openalex.org/W3101267588","https://openalex.org/W3106003309"],"related_works":["https://openalex.org/W2949778647","https://openalex.org/W2914147532","https://openalex.org/W2895217092","https://openalex.org/W3193497775","https://openalex.org/W2962889000","https://openalex.org/W2792924152","https://openalex.org/W2572908757","https://openalex.org/W3202820355","https://openalex.org/W3003326990","https://openalex.org/W2906003738","https://openalex.org/W3008118770","https://openalex.org/W2967199500","https://openalex.org/W2977862854","https://openalex.org/W2964352056","https://openalex.org/W3170487598","https://openalex.org/W2963704562","https://openalex.org/W2912998415","https://openalex.org/W3129365256","https://openalex.org/W2904077174","https://openalex.org/W3039982286"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"present":[4],"a":[5,89],"novel":[6],"approach":[7,85],"for":[8,47,93],"incorporating":[9],"external":[10],"knowledge":[11],"in":[12],"Recurrent":[13],"Neural":[14],"Networks":[15],"(RNNs).":[16],"We":[17,52],"propose":[18],"the":[19,25,36,40,43,48,70],"integration":[20],"of":[21,28,33,42,72],"lexicon":[22],"features":[23],"into":[24],"self-attention":[26],"mechanism":[27],"RNN-based":[29,94],"architectures.":[30],"This":[31],"form":[32],"conditioning":[34],"on":[35,65],"attention":[37],"distribution,":[38],"enforces":[39],"contribution":[41],"most":[44],"salient":[45],"words":[46],"task":[49],"at":[50],"hand.":[51],"introduce":[53],"three":[54],"methods,":[55],"namely":[56],"attentional":[57],"concatenation,":[58],"feature-based":[59,76],"gating":[60,77],"and":[61,100],"affine":[62],"transformation.":[63],"Experiments":[64],"six":[66],"benchmark":[67],"datasets":[68],"show":[69],"effectiveness":[71],"our":[73],"methods.":[74],"Attentional":[75],"yields":[78],"consistent":[79],"performance":[80],"improvement":[81],"across":[82],"tasks.":[83],"Our":[84],"is":[86],"implemented":[87],"as":[88],"simple":[90],"add-on":[91],"module":[92],"models":[95],"with":[96],"minimal":[97],"computational":[98],"overhead":[99],"can":[101],"be":[102],"adapted":[103],"to":[104],"any":[105],"deep":[106],"neural":[107],"architecture.":[108]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}