{"id":"https://openalex.org/W4392942643","doi":"https://doi.org/10.1109/bcd57833.2023.10466348","title":"Leveraging Unannotated Data to Improve Zero-Shot Question Answering in the French Legal Domain","display_name":"Leveraging Unannotated Data to Improve Zero-Shot Question Answering in the French Legal Domain","publication_year":2023,"publication_date":"2023-12-14","ids":{"openalex":"https://openalex.org/W4392942643","doi":"https://doi.org/10.1109/bcd57833.2023.10466348"},"language":"en","primary_location":{"id":"doi:10.1109/bcd57833.2023.10466348","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bcd57833.2023.10466348","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/ACIS 8th International Conference on Big Data, Cloud Computing, and Data Science (BCD)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5094188704","display_name":"Ahmed Touila","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ahmed Touila","raw_affiliation_strings":["Hyperlex/Dilitrust,Applied Research Team,Paris,France","Applied Research Team, Hyperlex/Dilitrust, Paris, France"],"affiliations":[{"raw_affiliation_string":"Hyperlex/Dilitrust,Applied Research Team,Paris,France","institution_ids":[]},{"raw_affiliation_string":"Applied Research Team, Hyperlex/Dilitrust, Paris, France","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102632115","display_name":"Elie Louis","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Elie Louis","raw_affiliation_strings":["Hyperlex/Dilitrust,Applied Research Team,Paris,France","Applied Research Team, Hyperlex/Dilitrust, Paris, France"],"affiliations":[{"raw_affiliation_string":"Hyperlex/Dilitrust,Applied Research Team,Paris,France","institution_ids":[]},{"raw_affiliation_string":"Applied Research Team, Hyperlex/Dilitrust, Paris, France","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034469447","display_name":"Hamza Gharbi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hamza Gharbi","raw_affiliation_strings":["Hyperlex/Dilitrust,Applied Research Team,Paris,France","Applied Research Team, Hyperlex/Dilitrust, Paris, France"],"affiliations":[{"raw_affiliation_string":"Hyperlex/Dilitrust,Applied Research Team,Paris,France","institution_ids":[]},{"raw_affiliation_string":"Applied Research Team, Hyperlex/Dilitrust, Paris, France","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5094188704"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.21247885,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"201","last_page":"207"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9984999895095825,"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":0.9984999895095825,"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":0.9768000245094299,"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":0.6768980026245117},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5299373865127563},{"id":"https://openalex.org/keywords/zero","display_name":"Zero (linguistics)","score":0.4756697714328766},{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.4365845322608948},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.42252466082572937},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41134777665138245},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13782542943954468},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.07253530621528625}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6768980026245117},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5299373865127563},{"id":"https://openalex.org/C2780813799","wikidata":"https://www.wikidata.org/wiki/Q3274237","display_name":"Zero (linguistics)","level":2,"score":0.4756697714328766},{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.4365845322608948},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.42252466082572937},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41134777665138245},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13782542943954468},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.07253530621528625},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bcd57833.2023.10466348","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bcd57833.2023.10466348","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/ACIS 8th International Conference on Big Data, Cloud Computing, and Data Science (BCD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W1967578387","https://openalex.org/W2270070752","https://openalex.org/W2762144331","https://openalex.org/W2896457183","https://openalex.org/W2912924812","https://openalex.org/W2949428332","https://openalex.org/W2951434086","https://openalex.org/W2953271402","https://openalex.org/W2962985038","https://openalex.org/W2963206679","https://openalex.org/W2963430447","https://openalex.org/W2963748441","https://openalex.org/W2965373594","https://openalex.org/W2986154550","https://openalex.org/W2996428491","https://openalex.org/W3038613107","https://openalex.org/W3041018801","https://openalex.org/W3099700870","https://openalex.org/W3099950029","https://openalex.org/W3103187652","https://openalex.org/W3104467951","https://openalex.org/W3124687886","https://openalex.org/W3135190223","https://openalex.org/W3185922622","https://openalex.org/W3205068155","https://openalex.org/W3207699717","https://openalex.org/W4205137784","https://openalex.org/W4206555128","https://openalex.org/W4226408727","https://openalex.org/W4252076394","https://openalex.org/W4288089799","https://openalex.org/W4292779060","https://openalex.org/W6755207826","https://openalex.org/W6760019105","https://openalex.org/W6764401283","https://openalex.org/W6766673545","https://openalex.org/W6768021236","https://openalex.org/W6769627184","https://openalex.org/W6778660954","https://openalex.org/W6778883912","https://openalex.org/W6791145691","https://openalex.org/W6802317279","https://openalex.org/W6802669662","https://openalex.org/W6804874140"],"related_works":["https://openalex.org/W2074502265","https://openalex.org/W4214877189","https://openalex.org/W2773965352","https://openalex.org/W2381179799","https://openalex.org/W2384605597","https://openalex.org/W2980279061","https://openalex.org/W2334685461","https://openalex.org/W2387743295","https://openalex.org/W2366718574","https://openalex.org/W2359774528"],"abstract_inverted_index":{"State":[0],"of":[1],"the":[2,31],"art":[3],"question":[4,57],"answering":[5,58],"models":[6],"have":[7,41],"recently":[8],"shown":[9],"impressive":[10],"performance":[11,78,84],"especially":[12],"in":[13,34,79,85],"a":[14,25,42,54,66],"zero-shot":[15,83],"setup.":[16],"This":[17],"approach":[18,59],"is":[19,37],"particularly":[20],"useful":[21],"when":[22],"confronted":[23],"with":[24],"highly":[26],"diverse":[27],"domain":[28],"such":[29],"as":[30,63,65],"legal":[32],"field,":[33],"which":[35],"it":[36],"increasingly":[38],"difficult":[39],"to":[40,60,70],"dataset":[43],"covering":[44],"every":[45],"notion":[46],"and":[47,74,81],"concept.":[48],"In":[49],"this":[50],"work,":[51],"we":[52],"propose":[53],"flexible":[55],"generative":[56],"contract":[61],"analysis":[62],"well":[64],"weakly":[67],"supervised":[68],"procedure":[69],"leverage":[71],"non-annotated":[72],"data":[73],"boost":[75],"our":[76],"models\u2019":[77],"general,":[80],"their":[82],"particular.":[86]},"counts_by_year":[],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}
