{"id":"https://openalex.org/W2963522904","doi":"https://doi.org/10.18653/v1/p19-1338","title":"An Imitation Learning Approach to Unsupervised Parsing","display_name":"An Imitation Learning Approach to Unsupervised Parsing","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2963522904","doi":"https://doi.org/10.18653/v1/p19-1338","mag":"2963522904"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p19-1338","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1338","pdf_url":"https://www.aclweb.org/anthology/P19-1338.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":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/P19-1338.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100387285","display_name":"Bowen Li","orcid":"https://orcid.org/0000-0002-6331-1629"},"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":true,"raw_author_name":"Bowen Li","raw_affiliation_strings":["Institute for Language, Cognition and Computation School of Informatics, University of Edinburgh, UK"],"affiliations":[{"raw_affiliation_string":"Institute for Language, Cognition and Computation School of Informatics, University of Edinburgh, UK","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024821632","display_name":"Lili Mou","orcid":"https://orcid.org/0000-0001-7753-4295"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Lili Mou","raw_affiliation_strings":["University of Waterloo, Canada"],"affiliations":[{"raw_affiliation_string":"University of Waterloo, Canada","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054936589","display_name":"Frank Keller","orcid":"https://orcid.org/0000-0002-8242-4362"},"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":"Frank Keller","raw_affiliation_strings":["Institute for Language, Cognition and Computation School of Informatics, University of Edinburgh, UK"],"affiliations":[{"raw_affiliation_string":"Institute for Language, Cognition and Computation School of Informatics, University of Edinburgh, UK","institution_ids":["https://openalex.org/I98677209"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100387285"],"corresponding_institution_ids":["https://openalex.org/I98677209"],"apc_list":null,"apc_paid":null,"fwci":2.0232,"has_fulltext":true,"cited_by_count":18,"citation_normalized_percentile":{"value":0.9008835,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3485","last_page":"3492"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9998999834060669,"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":0.992900013923645,"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":0.8617018461227417},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7901731729507446},{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.7222005128860474},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6484382748603821},{"id":"https://openalex.org/keywords/bottom-up-parsing","display_name":"Bottom-up parsing","score":0.611533522605896},{"id":"https://openalex.org/keywords/dependency-grammar","display_name":"Dependency grammar","score":0.5643892288208008},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.48520806431770325},{"id":"https://openalex.org/keywords/heuristics","display_name":"Heuristics","score":0.473497211933136},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.4688381254673004},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.46195435523986816},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.4611625075340271},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.453048437833786},{"id":"https://openalex.org/keywords/top-down-parsing","display_name":"Top-down parsing","score":0.4459609389305115},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.43351346254348755},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.432902067899704},{"id":"https://openalex.org/keywords/top-down-parsing-language","display_name":"Top-down parsing language","score":0.4194568395614624},{"id":"https://openalex.org/keywords/syntax","display_name":"Syntax","score":0.418123722076416}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8617018461227417},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7901731729507446},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.7222005128860474},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6484382748603821},{"id":"https://openalex.org/C60690694","wikidata":"https://www.wikidata.org/wiki/Q894902","display_name":"Bottom-up parsing","level":4,"score":0.611533522605896},{"id":"https://openalex.org/C164883195","wikidata":"https://www.wikidata.org/wiki/Q674834","display_name":"Dependency grammar","level":3,"score":0.5643892288208008},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.48520806431770325},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.473497211933136},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.4688381254673004},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.46195435523986816},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.4611625075340271},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.453048437833786},{"id":"https://openalex.org/C42560504","wikidata":"https://www.wikidata.org/wiki/Q15419395","display_name":"Top-down parsing","level":3,"score":0.4459609389305115},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.43351346254348755},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.432902067899704},{"id":"https://openalex.org/C166651950","wikidata":"https://www.wikidata.org/wiki/Q7824365","display_name":"Top-down parsing language","level":5,"score":0.4194568395614624},{"id":"https://openalex.org/C60048249","wikidata":"https://www.wikidata.org/wiki/Q37437","display_name":"Syntax","level":2,"score":0.418123722076416},{"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/p19-1338","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1338","pdf_url":"https://www.aclweb.org/anthology/P19-1338.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"}],"best_oa_location":{"id":"doi:10.18653/v1/p19-1338","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1338","pdf_url":"https://www.aclweb.org/anthology/P19-1338.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":[{"id":"https://metadata.un.org/sdg/4","score":0.75,"display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G2126551001","display_name":null,"funder_award_id":"Fellowship","funder_id":"https://openalex.org/F4320319993","funder_display_name":"Leverhulme Trust"}],"funders":[{"id":"https://openalex.org/F4320319993","display_name":"Leverhulme Trust","ror":"https://ror.org/012mzw131"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2963522904.pdf","grobid_xml":"https://content.openalex.org/works/W2963522904.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W1601637950","https://openalex.org/W1840435438","https://openalex.org/W2250531756","https://openalex.org/W2251939518","https://openalex.org/W2547875792","https://openalex.org/W2604382266","https://openalex.org/W2619818172","https://openalex.org/W2785379783","https://openalex.org/W2791751435","https://openalex.org/W2859444450","https://openalex.org/W2889260178","https://openalex.org/W2891632051","https://openalex.org/W2932376173","https://openalex.org/W2932637973","https://openalex.org/W2951699762","https://openalex.org/W2952576443","https://openalex.org/W2962843521","https://openalex.org/W2962942784","https://openalex.org/W2963233086","https://openalex.org/W2963355447","https://openalex.org/W2963363446","https://openalex.org/W2963411763","https://openalex.org/W2963451457","https://openalex.org/W2963580443","https://openalex.org/W2963648186","https://openalex.org/W2963754491","https://openalex.org/W2963846996","https://openalex.org/W2963863610","https://openalex.org/W2964224278","https://openalex.org/W2964263959","https://openalex.org/W4289373464","https://openalex.org/W4299674251"],"related_works":["https://openalex.org/W3088470625","https://openalex.org/W3035970863","https://openalex.org/W2250574586","https://openalex.org/W2389755172","https://openalex.org/W2058621701","https://openalex.org/W2914096745","https://openalex.org/W2152451097","https://openalex.org/W1996016640","https://openalex.org/W2381769141","https://openalex.org/W3096367574"],"abstract_inverted_index":{"Recently,":[0],"there":[1],"has":[2],"been":[3],"an":[4,49],"increasing":[5],"interest":[6],"in":[7,41,109],"unsupervised":[8,54],"parsers":[9],"that":[10,100],"optimize":[11],"semantically":[12,84],"oriented":[13,85],"objectives,":[14],"typically":[15],"using":[16],"reinforcement":[17],"learning.":[18],"Unfortunately,":[19],"the":[20,59,64,92,107,120],"learned":[21],"trees":[22,29],"often":[23],"do":[24],"not":[25,39],"match":[26],"actual":[27],"syntax":[28],"well.":[30],"Also,":[31],"their":[32],"model":[33,69],"lacks":[34],"interpretability":[35],"as":[36],"it":[37,101],"is":[38,76],"grounded":[40],"parsing":[42,72,112],"actions.":[43,73],"In":[44],"our":[45,89,116],"work,":[46],"we":[47,57],"propose":[48],"imitation":[50],"learning":[51],"approach":[52,90],"to":[53,66],"parsing,":[55],"where":[56],"transfer":[58],"syntactic":[60],"knowledge":[61],"induced":[62],"by":[63,79],"PRPN":[65],"a":[67,83,103],"Tree-LSTM":[68],"with":[70],"discrete":[71],"Its":[74],"policy":[75],"then":[77],"refined":[78],"Gumbel-Softmax":[80],"training":[81],"towards":[82],"objective.":[86],"We":[87],"evaluate":[88],"on":[91],"All":[93],"Natural":[94],"Language":[95],"Inference":[96],"dataset":[97],"and":[98],"show":[99],"achieves":[102],"new":[104],"state":[105],"of":[106,111],"art":[108],"terms":[110],"F":[113],"-score,":[114],"outperforming":[115],"base":[117],"models,":[118],"including":[119],"PRPN.":[121],"1":[122]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":3}],"updated_date":"2026-04-12T07:58:50.170612","created_date":"2025-10-10T00:00:00"}