{"id":"https://openalex.org/W4385573708","doi":"https://doi.org/10.18653/v1/2022.emnlp-main.820","title":"Injecting Domain Knowledge in Language Models for Task-oriented Dialogue Systems","display_name":"Injecting Domain Knowledge in Language Models for Task-oriented Dialogue Systems","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4385573708","doi":"https://doi.org/10.18653/v1/2022.emnlp-main.820"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2022.emnlp-main.820","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2022.emnlp-main.820","pdf_url":"https://aclanthology.org/2022.emnlp-main.820.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 2022 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://aclanthology.org/2022.emnlp-main.820.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5060107290","display_name":"Denis Emelin","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":true,"raw_author_name":"Denis Emelin","raw_affiliation_strings":["University of Edinburgh ,"],"affiliations":[{"raw_affiliation_string":"University of Edinburgh ,","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082823549","display_name":"Daniele Bonadiman","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Daniele Bonadiman","raw_affiliation_strings":["AWS AI Labs , {dbonadim,"],"affiliations":[{"raw_affiliation_string":"AWS AI Labs , {dbonadim,","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051917159","display_name":"Sawsan Alqahtani","orcid":null},"institutions":[{"id":"https://openalex.org/I106778892","display_name":"Princess Nourah bint Abdulrahman University","ror":"https://ror.org/05b0cyh02","country_code":"SA","type":"education","lineage":["https://openalex.org/I106778892"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Sawsan Alqahtani","raw_affiliation_strings":["National Center of AI ,","Princess Nourah Bint Abdulrahman"],"affiliations":[{"raw_affiliation_string":"National Center of AI ,","institution_ids":[]},{"raw_affiliation_string":"Princess Nourah Bint Abdulrahman","institution_ids":["https://openalex.org/I106778892"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100388333","display_name":"Yi Zhang","orcid":"https://orcid.org/0000-0003-4299-1511"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yi Zhang","raw_affiliation_strings":["AWS AI Labs , {dbonadim,"],"affiliations":[{"raw_affiliation_string":"AWS AI Labs , {dbonadim,","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070002963","display_name":"Saab Mansour","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Saab Mansour","raw_affiliation_strings":["AWS AI Labs , {dbonadim,"],"affiliations":[{"raw_affiliation_string":"AWS AI Labs , {dbonadim,","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5060107290"],"corresponding_institution_ids":["https://openalex.org/I98677209"],"apc_list":null,"apc_paid":null,"fwci":1.194,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.82775108,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"11962","last_page":"11974"},"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/T12031","display_name":"Speech and dialogue systems","score":0.9940000176429749,"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":0.9934999942779541,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8177894353866577},{"id":"https://openalex.org/keywords/domain-knowledge","display_name":"Domain knowledge","score":0.7043003439903259},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6725436449050903},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5585734248161316},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5274617671966553},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4949745535850525},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.42965489625930786},{"id":"https://openalex.org/keywords/knowledge-based-systems","display_name":"Knowledge-based systems","score":0.4124416410923004},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36785733699798584},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07894867658615112}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8177894353866577},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.7043003439903259},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6725436449050903},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5585734248161316},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5274617671966553},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4949745535850525},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.42965489625930786},{"id":"https://openalex.org/C115925183","wikidata":"https://www.wikidata.org/wiki/Q1412694","display_name":"Knowledge-based systems","level":2,"score":0.4124416410923004},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36785733699798584},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07894867658615112},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2022.emnlp-main.820","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2022.emnlp-main.820","pdf_url":"https://aclanthology.org/2022.emnlp-main.820.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 2022 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2022.emnlp-main.820","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2022.emnlp-main.820","pdf_url":"https://aclanthology.org/2022.emnlp-main.820.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 2022 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.4300000071525574}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4385573708.pdf"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W2896457183","https://openalex.org/W2908510526","https://openalex.org/W2964006684","https://openalex.org/W2964303773","https://openalex.org/W2970476646","https://openalex.org/W2970597249","https://openalex.org/W2972119829","https://openalex.org/W2980282514","https://openalex.org/W3034999214","https://openalex.org/W3045703328","https://openalex.org/W3099453223","https://openalex.org/W3100353583","https://openalex.org/W3134891661","https://openalex.org/W3164652135","https://openalex.org/W3171434230","https://openalex.org/W3175604467","https://openalex.org/W3197780238","https://openalex.org/W3200895474","https://openalex.org/W4287366208","https://openalex.org/W4287684041","https://openalex.org/W4287795696","https://openalex.org/W4292779060","https://openalex.org/W4389009440"],"related_works":["https://openalex.org/W3098003361","https://openalex.org/W2475408106","https://openalex.org/W1583422155","https://openalex.org/W2086580554","https://openalex.org/W2553860513","https://openalex.org/W3213252596","https://openalex.org/W3045387744","https://openalex.org/W1649619740","https://openalex.org/W1480876128","https://openalex.org/W631902903"],"abstract_inverted_index":{"Pre-trained":[0],"language":[1],"models":[2],"(PLM)":[3],"have":[4],"advanced":[5],"the":[6,71,110,137],"state-of-the-art":[7],"across":[8],"NLP":[9,33],"applications,":[10],"but":[11],"lack":[12],"domain-specific":[13,75],"knowledge":[14,29,36,55,76,114,144],"that":[15,57,90],"does":[16],"not":[17],"naturally":[18],"occur":[19],"in":[20,40,48,60],"pre-training":[21],"data.":[22],"Previous":[23],"studies":[24,42],"augmented":[25],"PLMs":[26,96],"with":[27,95,146],"symbolic":[28],"for":[30,102,130],"different":[31,106],"downstream":[32],"tasks.":[34,82],"However,":[35],"bases":[37,56],"(KBs)":[38],"utilized":[39],"these":[41],"are":[43,58],"usually":[44],"large-scale":[45],"and":[46,53,97,136],"static,":[47],"contrast":[49],"to":[50,78],"small,":[51],"domain-specific,":[52],"modifiable":[54],"prominent":[59],"real-world":[61],"task-oriented":[62],"dialogue":[63],"(TOD)":[64],"systems.":[65],"In":[66],"this":[67,84],"paper,":[68],"we":[69,86,117],"showcase":[70],"advantages":[72],"of":[73,112,143],"injecting":[74],"prior":[77],"fine-tuning":[79],"on":[80,134],"TOD":[81,131],"To":[83,108],"end,":[85],"utilize":[87],"light-weight":[88],"adapters":[89,147],"can":[91],"be":[92],"easily":[93],"integrated":[94],"serve":[98],"as":[99],"a":[100,126],"repository":[101],"facts":[103],"learned":[104],"from":[105],"KBs.":[107],"measure":[109],"efficacy":[111],"proposed":[113],"injection":[115,145],"methods,":[116],"introduce":[118],"Knowledge":[119],"Probing":[120],"using":[121],"Response":[122],"Selection":[123],"(KPRS)":[124],"\u2013":[125],"probe":[127],"designed":[128],"specifically":[129],"models.":[132],"Experiments":[133],"KPRS":[135],"response":[138],"generation":[139],"task":[140],"show":[141],"improvements":[142],"over":[148],"strong":[149],"baselines.":[150]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":3}],"updated_date":"2026-01-24T23:23:39.755997","created_date":"2025-10-10T00:00:00"}