{"id":"https://openalex.org/W2890909908","doi":"https://doi.org/10.18653/v1/d18-1065","title":"Surprisingly Easy Hard-Attention for Sequence to Sequence Learning","display_name":"Surprisingly Easy Hard-Attention for Sequence to Sequence Learning","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2890909908","doi":"https://doi.org/10.18653/v1/d18-1065","mag":"2890909908"},"language":"en","primary_location":{"id":"doi:10.18653/v1/d18-1065","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d18-1065","pdf_url":"https://www.aclweb.org/anthology/D18-1065.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 2018 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/D18-1065.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103980935","display_name":"Shiv Shankar","orcid":null},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Shiv Shankar","raw_affiliation_strings":["IIT Bombay"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IIT Bombay","institution_ids":["https://openalex.org/I162827531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064222284","display_name":"Siddhant Garg","orcid":"https://orcid.org/0009-0004-0219-511X"},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Siddhant Garg","raw_affiliation_strings":["IIT Bombay"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IIT Bombay","institution_ids":["https://openalex.org/I162827531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031035935","display_name":"Sunita Sarawagi","orcid":"https://orcid.org/0009-0005-9538-6616"},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sunita Sarawagi","raw_affiliation_strings":["IIT Bombay"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IIT Bombay","institution_ids":["https://openalex.org/I162827531"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I162827531"],"apc_list":null,"apc_paid":null,"fwci":5.2384,"has_fulltext":true,"cited_by_count":41,"citation_normalized_percentile":{"value":0.96369648,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9994000196456909,"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":0.9991999864578247,"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":0.801852822303772},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.795526385307312},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.6544755697250366},{"id":"https://openalex.org/keywords/sequence-learning","display_name":"Sequence learning","score":0.5711100697517395},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4991180896759033},{"id":"https://openalex.org/keywords/machine-translation","display_name":"Machine translation","score":0.483347624540329},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.4831080436706543},{"id":"https://openalex.org/keywords/translation","display_name":"Translation (biology)","score":0.43843013048171997}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.801852822303772},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.795526385307312},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.6544755697250366},{"id":"https://openalex.org/C40506919","wikidata":"https://www.wikidata.org/wiki/Q7452469","display_name":"Sequence learning","level":2,"score":0.5711100697517395},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4991180896759033},{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.483347624540329},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.4831080436706543},{"id":"https://openalex.org/C149364088","wikidata":"https://www.wikidata.org/wiki/Q185917","display_name":"Translation (biology)","level":4,"score":0.43843013048171997},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C105580179","wikidata":"https://www.wikidata.org/wiki/Q188928","display_name":"Messenger RNA","level":3,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/d18-1065","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d18-1065","pdf_url":"https://www.aclweb.org/anthology/D18-1065.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 2018 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/d18-1065","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d18-1065","pdf_url":"https://www.aclweb.org/anthology/D18-1065.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 2018 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2890909908.pdf","grobid_xml":"https://content.openalex.org/works/W2890909908.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W1514535095","https://openalex.org/W1522301498","https://openalex.org/W1642393990","https://openalex.org/W1902237438","https://openalex.org/W2125308790","https://openalex.org/W2133564696","https://openalex.org/W2253795368","https://openalex.org/W2576482813","https://openalex.org/W2619122421","https://openalex.org/W2625720409","https://openalex.org/W2757291580","https://openalex.org/W2768763386","https://openalex.org/W2774761636","https://openalex.org/W2782917850","https://openalex.org/W2905927205","https://openalex.org/W2953830716","https://openalex.org/W2962811598","https://openalex.org/W2963123301","https://openalex.org/W2963403868","https://openalex.org/W2963502387","https://openalex.org/W2963513950","https://openalex.org/W2963537482","https://openalex.org/W2963876447","https://openalex.org/W2963888305","https://openalex.org/W2964045208","https://openalex.org/W2964121744","https://openalex.org/W2964260331","https://openalex.org/W2964308564","https://openalex.org/W3041866211","https://openalex.org/W3204130541","https://openalex.org/W4230563027","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W3011059803","https://openalex.org/W3151736118","https://openalex.org/W2012531322","https://openalex.org/W4362495644","https://openalex.org/W2883671469","https://openalex.org/W2883195674","https://openalex.org/W2072736607","https://openalex.org/W2125171914","https://openalex.org/W3080374445","https://openalex.org/W2964790801"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"we":[3,57],"show":[4,58],"that":[5],"a":[6],"simple":[7],"beam":[8],"approximation":[9],"of":[10,36,46],"the":[11,34,43],"joint":[12],"distribution":[13],"between":[14],"attention":[15,24,41,68],"and":[16,22,42,52,60],"output":[17],"is":[18],"an":[19],"easy,":[20],"accurate,":[21],"efficient":[23],"mechanism":[25],"for":[26],"sequence":[27,29],"to":[28,66],"learning.":[30],"The":[31],"method":[32],"combines":[33],"advantage":[35],"sharp":[37],"focus":[38],"in":[39,63],"hard":[40],"implementation":[44],"ease":[45],"soft":[47],"attention.":[48],"On":[49],"five":[50],"translation":[51],"two":[53],"morphological":[54],"inflection":[55],"tasks":[56],"effortless":[59],"consistent":[61],"gains":[62],"BLEU":[64],"compared":[65],"existing":[67],"mechanisms.":[69]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":15},{"year":2018,"cited_by_count":2}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}