{"id":"https://openalex.org/W4412889626","doi":"https://doi.org/10.18653/v1/2025.acl-long.1517","title":"\ud835\udeff-Stance: A Large-Scale Real World Dataset of Stances in Legal Argumentation","display_name":"\ud835\udeff-Stance: A Large-Scale Real World Dataset of Stances in Legal Argumentation","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412889626","doi":"https://doi.org/10.18653/v1/2025.acl-long.1517"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2025.acl-long.1517","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.acl-long.1517","pdf_url":"https://aclanthology.org/2025.acl-long.1517.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 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.acl-long.1517.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012994458","display_name":"Ankita Gupta","orcid":"https://orcid.org/0000-0001-8415-8822"},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ankita Gupta","raw_affiliation_strings":["University of Massachusetts Amherst"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Massachusetts Amherst","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054845562","display_name":"Douglas Rice","orcid":"https://orcid.org/0000-0002-3653-857X"},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Douglas Rice","raw_affiliation_strings":["University of Massachusetts Amherst"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Massachusetts Amherst","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"last","author":{"id":null,"display_name":"Brendan O\u2019Connor","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Brendan O\u2019Connor","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":17.1088,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.98810162,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"31450","last_page":"31467"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13643","display_name":"Artificial Intelligence in Law","score":0.9865000247955322,"subfield":{"id":"https://openalex.org/subfields/3320","display_name":"Political Science and International Relations"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T13643","display_name":"Artificial Intelligence in Law","score":0.9865000247955322,"subfield":{"id":"https://openalex.org/subfields/3320","display_name":"Political Science and International Relations"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T14012","display_name":"Comparative and International Law Studies","score":0.9296000003814697,"subfield":{"id":"https://openalex.org/subfields/3308","display_name":"Law"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/argumentation-theory","display_name":"Argumentation theory","score":0.7658315300941467},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.641147255897522},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5442155003547668},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.39478254318237305},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35284745693206787},{"id":"https://openalex.org/keywords/epistemology","display_name":"Epistemology","score":0.20738208293914795},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.15671339631080627},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.12395250797271729},{"id":"https://openalex.org/keywords/philosophy","display_name":"Philosophy","score":0.08384042978286743}],"concepts":[{"id":"https://openalex.org/C65059942","wikidata":"https://www.wikidata.org/wiki/Q270105","display_name":"Argumentation theory","level":2,"score":0.7658315300941467},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.641147255897522},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5442155003547668},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.39478254318237305},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35284745693206787},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.20738208293914795},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.15671339631080627},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.12395250797271729},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.08384042978286743}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.acl-long.1517","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.acl-long.1517","pdf_url":"https://aclanthology.org/2025.acl-long.1517.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 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.acl-long.1517","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.acl-long.1517","pdf_url":"https://aclanthology.org/2025.acl-long.1517.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 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.5699999928474426}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412889626.pdf","grobid_xml":"https://content.openalex.org/works/W4412889626.grobid-xml"},"referenced_works_count":1,"referenced_works":["https://openalex.org/W3204410951"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4256185029","https://openalex.org/W2141332034","https://openalex.org/W4388437769","https://openalex.org/W2762454042","https://openalex.org/W2064153856","https://openalex.org/W2337488240","https://openalex.org/W52290235"],"abstract_inverted_index":{"We":[0],"present":[1],"-Stance,":[2],"a":[3,48,54],"large-scale":[4],"dataset":[5,32,187],"of":[6,20,22,66,86,170],"stances":[7],"involved":[8],"in":[9,27,152,160],"legal":[10,39,55,138,194],"argumentation.-Stance":[11],"contains":[12],"stance-annotated":[13],"argument":[14,40,56,195],"pairs,":[15],"semi-automatically":[16],"mined":[17],"from":[18],"millions":[19],"examples":[21],"U.S.":[23],"judges":[24],"citing":[25],"precedent":[26],"context":[28],"using":[29,128],"citation":[30],"signals.The":[31],"aims":[33],"to":[34,59,113,189],"facilitate":[35],"work":[36],"on":[37,92,109,147,193],"the":[38,64,137,168,179,185],"stance":[41,104],"classification":[42],"task,":[43,68],"which":[44],"involves":[45],"assessing":[46],"whether":[47],"case":[49],"summary":[50],"strengthens":[51],"or":[52],"weakens":[53],"(polarity)":[57],"and":[58,83,125,181],"what":[60],"extent":[61],"(intensity).To":[62],"assess":[63],"complexity":[65],"this":[67],"we":[69,140,155],"evaluate":[70],"various":[71],"existing":[72],"NLP":[73],"methods,":[74],"including":[75],"zero-shot":[76,126],"prompting":[77,98,127],"proprietary":[78,99],"large":[79],"language":[80,89],"models":[81,90],"(LLMs),":[82],"supervised":[84,106],"finetuning":[85,108],"smaller":[87],"open-weight":[88],"(LMs)":[91],"-Stance.Our":[93],"findings":[94],"reveal":[95],"that":[96,118,143],"although":[97],"LLMs":[100],"can":[101,163],"help":[102],"predict":[103],"polarity,":[105],"model":[107,165],"-Stance":[110,148],"is":[111],"necessary":[112],"distinguish":[114],"intensity.We":[115],"further":[116,141,191],"find":[117,142],"alternative":[119],"strategies":[120],"such":[121],"as":[122],"domain-specific":[123],"pretraining":[124],"masked":[129],"LMs":[130,146],"remain":[131],"insufficient.Beyond":[132],"our":[133],"dataset's":[134],"utility":[135],"for":[136,174],"domain,":[139],"fine-tuning":[144],"small":[145],"improves":[149],"their":[150],"performance":[151],"other":[153],"domains.Finally,":[154],"study":[156],"how":[157],"temporal":[158],"changes":[159],"signal":[161],"definition":[162],"impact":[164],"performance,":[166],"highlighting":[167],"importance":[169],"careful":[171],"data":[172],"curation":[173],"downstream":[175],"tasks":[176],"by":[177],"considering":[178],"historical":[180],"sociocultural":[182],"context.We":[183],"publish":[184],"associated":[186],"1":[188],"foster":[190],"research":[192],"reasoning.":[196]},"counts_by_year":[{"year":2026,"cited_by_count":3}],"updated_date":"2026-08-18T07:49:30.821534","created_date":"2025-10-10T00:00:00"}
