{"id":"https://openalex.org/W4403786794","doi":"https://doi.org/10.48550/arxiv.2409.15825","title":"60 Data Points are Sufficient to Fine-Tune LLMs for Question-Answering","display_name":"60 Data Points are Sufficient to Fine-Tune LLMs for Question-Answering","publication_year":2024,"publication_date":"2024-09-24","ids":{"openalex":"https://openalex.org/W4403786794","doi":"https://doi.org/10.48550/arxiv.2409.15825"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2409.15825","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2409.15825","pdf_url":"https://arxiv.org/pdf/2409.15825","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2409.15825","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100777718","display_name":"Junjie Ye","orcid":"https://orcid.org/0009-0004-0921-6323"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ye, Junjie","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100958962","display_name":"Yuming Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Yuming","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101829098","display_name":"Qi Zhang","orcid":"https://orcid.org/0000-0002-3586-1164"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Qi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058353652","display_name":"Tao Gui","orcid":"https://orcid.org/0000-0002-6154-0751"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gui, Tao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088834359","display_name":"Xuanjing Huang","orcid":"https://orcid.org/0000-0001-9197-9426"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Xuanjing","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100395978","display_name":"Peng Wang","orcid":"https://orcid.org/0000-0002-1328-5784"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Peng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101873354","display_name":"Zhongchao Shi","orcid":"https://orcid.org/0000-0002-5216-3827"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shi, Zhongchao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Fan, Jianping","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fan, Jianping","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5100777718"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"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/T13274","display_name":"Expert finding and Q&A systems","score":0.9815000295639038,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.9642000198364258,"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/question-answering","display_name":"Question answering","score":0.766575813293457},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5004398822784424},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.428340345621109},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.37751758098602295},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33611440658569336},{"id":"https://openalex.org/keywords/philosophy","display_name":"Philosophy","score":0.13517531752586365}],"concepts":[{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.766575813293457},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5004398822784424},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.428340345621109},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.37751758098602295},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33611440658569336},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.13517531752586365}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2409.15825","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2409.15825","pdf_url":"https://arxiv.org/pdf/2409.15825","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2409.15825","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2409.15825","pdf_url":null,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2409.15825","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2409.15825","pdf_url":"https://arxiv.org/pdf/2409.15825","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4403786794.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2384605597","https://openalex.org/W2387743295","https://openalex.org/W3082787378","https://openalex.org/W2136007095","https://openalex.org/W2366230879","https://openalex.org/W3208425359","https://openalex.org/W3204019825"],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2],"(LLMs)":[3],"encode":[4],"extensive":[5],"world":[6],"knowledge":[7,51,119],"through":[8],"pre-training":[9],"on":[10,47,75,92,142,151],"massive":[11],"datasets,":[12],"which":[13],"can":[14,116],"then":[15],"be":[16],"fine-tuned":[17],"for":[18,26,29,84],"the":[19,30,48,54,79,86,113,118,127,146,152,163],"question-answering":[20],"(QA)":[21],"task.":[22,129],"However,":[23],"effective":[24],"strategies":[25],"fine-tuning":[27,43],"LLMs":[28,56,68,124],"QA":[31,128],"task":[32],"remain":[33],"largely":[34],"unexplored.":[35],"To":[36],"address":[37],"this":[38],"gap,":[39],"we":[40],"categorize":[41],"supervised":[42],"(SFT)":[44],"data":[45,82,97,110,133],"based":[46,150],"extent":[49],"of":[50,61,81,88,134],"memorized":[52],"by":[53],"pretrained":[55],"and":[57,95],"conduct":[58],"a":[59,139],"series":[60],"empirical":[62],"analyses.":[63],"Our":[64],"experiments,":[65],"involving":[66],"four":[67],"from":[69],"three":[70,76],"different":[71,89],"model":[72,93,154],"families,":[73],"focus":[74],"key":[77],"factors:":[78],"amount":[80],"required":[83],"SFT,":[85],"impact":[87,141],"SFT":[90,114,131],"datasets":[91],"performance,":[94,144],"how":[96],"requirements":[98],"vary":[99],"across":[100],"LLMs.":[101],"The":[102],"results":[103],"show":[104],"that":[105],"as":[106,108],"few":[107],"60":[109],"points":[111],"during":[112,121],"stage":[115],"activate":[117],"encoded":[120],"pre-training,":[122],"enabling":[123],"to":[125],"perform":[126],"Additionally,":[130],"with":[132,145],"varying":[135],"memory":[136],"levels":[137],"has":[138],"significant":[140],"LLM":[143],"optimal":[147],"dataset":[148],"differing":[149],"specific":[153],"being":[155],"fine-tuned.":[156],"Future":[157],"research":[158],"will":[159],"delve":[160],"deeper":[161],"into":[162],"mechanisms":[164],"underlying":[165],"these":[166],"phenomena.":[167]},"counts_by_year":[],"updated_date":"2026-03-25T23:56:10.502304","created_date":"2024-10-26T00:00:00"}
