{"id":"https://openalex.org/W4403995414","doi":"https://doi.org/10.1145/3677052.3698682","title":"FinQAPT: Empowering Financial Decisions with End-to-End LLM-driven Question Answering Pipeline","display_name":"FinQAPT: Empowering Financial Decisions with End-to-End LLM-driven Question Answering Pipeline","publication_year":2024,"publication_date":"2024-11-14","ids":{"openalex":"https://openalex.org/W4403995414","doi":"https://doi.org/10.1145/3677052.3698682"},"language":"en","primary_location":{"id":"doi:10.1145/3677052.3698682","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3677052.3698682","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3677052.3698682","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 5th ACM International Conference on AI in Finance","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3677052.3698682","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022533727","display_name":"Karam Singh","orcid":null},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Kuldeep Singh","raw_affiliation_strings":["Department of Statistics, Michigan State University, US"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Michigan State University, US","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031351140","display_name":"Simerjot Kaur","orcid":"https://orcid.org/0000-0002-5863-4749"},"institutions":[{"id":"https://openalex.org/I1305429384","display_name":"JPMorgan Chase & Co (United States)","ror":"https://ror.org/01x3kkr08","country_code":"US","type":"company","lineage":["https://openalex.org/I1305429384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Simerjot Kaur","raw_affiliation_strings":["JP Morgan Chase, US"],"affiliations":[{"raw_affiliation_string":"JP Morgan Chase, US","institution_ids":["https://openalex.org/I1305429384"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070646187","display_name":"Charese Smiley","orcid":"https://orcid.org/0009-0007-5575-2313"},"institutions":[{"id":"https://openalex.org/I1305429384","display_name":"JPMorgan Chase & Co (United States)","ror":"https://ror.org/01x3kkr08","country_code":"US","type":"company","lineage":["https://openalex.org/I1305429384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Charese Smiley","raw_affiliation_strings":["JP Morgan Chase, US"],"affiliations":[{"raw_affiliation_string":"JP Morgan Chase, US","institution_ids":["https://openalex.org/I1305429384"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5022533727"],"corresponding_institution_ids":["https://openalex.org/I87216513"],"apc_list":null,"apc_paid":null,"fwci":2.0851,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.89212759,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"266","last_page":"273"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9975000023841858,"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":0.9975000023841858,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9710999727249146,"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":0.9700999855995178,"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/pipeline","display_name":"Pipeline (software)","score":0.7178611755371094},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.6572892665863037},{"id":"https://openalex.org/keywords/end-to-end-principle","display_name":"End-to-end principle","score":0.6536743640899658},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5085321664810181},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.36114931106567383},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.32403087615966797},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1769847571849823},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.08665964007377625}],"concepts":[{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.7178611755371094},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.6572892665863037},{"id":"https://openalex.org/C74296488","wikidata":"https://www.wikidata.org/wiki/Q2527392","display_name":"End-to-end principle","level":2,"score":0.6536743640899658},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5085321664810181},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.36114931106567383},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.32403087615966797},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1769847571849823},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.08665964007377625}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3677052.3698682","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3677052.3698682","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3677052.3698682","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 5th ACM International Conference on AI in Finance","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2410.13959","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2410.13959","pdf_url":"https://arxiv.org/pdf/2410.13959","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3677052.3698682","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3677052.3698682","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3677052.3698682","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 5th ACM International Conference on AI in Finance","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.6600000262260437,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4403995414.pdf"},"referenced_works_count":15,"referenced_works":["https://openalex.org/W1978394996","https://openalex.org/W2560674852","https://openalex.org/W2890894339","https://openalex.org/W2951434086","https://openalex.org/W2962985038","https://openalex.org/W2970641574","https://openalex.org/W3118722740","https://openalex.org/W4205508242","https://openalex.org/W4252076394","https://openalex.org/W4289377895","https://openalex.org/W4385572980","https://openalex.org/W4386566488","https://openalex.org/W4389520103","https://openalex.org/W4391631359","https://openalex.org/W4392632244"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2384605597","https://openalex.org/W2151749779","https://openalex.org/W2387743295","https://openalex.org/W3179968364","https://openalex.org/W3082787378","https://openalex.org/W2136007095","https://openalex.org/W2366230879","https://openalex.org/W3208425359","https://openalex.org/W2349927912"],"abstract_inverted_index":{"Financial":[0],"decision-making":[1],"hinges":[2],"on":[3,39,112],"the":[4,11,17,32,57,66,72,98,105,121,148],"analysis":[5,143],"of":[6,14,34,68,102,117,144],"relevant":[7,35,133],"information":[8],"embedded":[9],"in":[10,16,131],"enormous":[12],"volume":[13],"documents":[15],"financial":[18,36,136,166],"domain.":[19],"To":[20,55],"address":[21],"this":[22],"challenge,":[23],"we":[24,59,108,124],"developed":[25],"FinQAPT,":[26],"an":[27,115],"end-to-end":[28,149],"pipeline":[29,122],"that":[30,154],"streamlines":[31],"identification":[33],"reports":[37],"based":[38],"a":[40,77,88,140,160],"query,":[41],"extracts":[42],"pertinent":[43],"context,":[44],"and":[45,87,147],"leverages":[46],"Large":[47],"Language":[48],"Models":[49],"(LLMs)":[50],"to":[51,64,83,96,129,158],"perform":[52],"downstream":[53],"tasks.":[54,167],"evaluate":[56],"pipeline,":[58,150],"experimented":[60],"with":[61],"various":[62],"techniques":[63],"optimize":[65],"performance":[67,127],"each":[69,145],"module":[70,106,146],"using":[71],"FinQA":[73],"dataset.":[74],"We":[75,138],"introduced":[76],"novel":[78,89],"clustering-based":[79],"negative":[80],"sampling":[81],"technique":[82],"enhance":[84],"context":[85,134],"extraction":[86],"prompting":[90],"method":[91],"called":[92],"Dynamic":[93],"N-shot":[94],"Prompting":[95],"boost":[97],"numerical":[99],"question-answering":[100],"capabilities":[101],"LLMs.":[103],"At":[104],"level,":[107,123],"achieved":[109],"state-of-the-art":[110],"accuracy":[111,116],"FinQA,":[113],"attaining":[114],"80.6%.":[118],"However,":[119],"at":[120],"observed":[125],"decreased":[126],"due":[128],"challenges":[130,153],"extracting":[132],"from":[135],"reports.":[137],"conducted":[139],"detailed":[141],"error":[142],"pinpointing":[151],"specific":[152],"must":[155],"be":[156],"addressed":[157],"develop":[159],"robust":[161],"solution":[162],"for":[163],"handling":[164],"complex":[165]},"counts_by_year":[{"year":2025,"cited_by_count":6}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}