{"id":"https://openalex.org/W7131090437","doi":"https://doi.org/10.48550/arxiv.2602.17937","title":"Analyzing LLM Instruction Optimization for Tabular Fact Verification","display_name":"Analyzing LLM Instruction Optimization for Tabular Fact Verification","publication_year":2026,"publication_date":"2026-02-20","ids":{"openalex":"https://openalex.org/W7131090437","doi":"https://doi.org/10.48550/arxiv.2602.17937"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.17937","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"Article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102684534","display_name":"Xiaotang Du","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Du, Xiaotang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126656652","display_name":"Giwon Hong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hong, Giwon","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068169387","display_name":"Wai-Chung Kwan","orcid":"https://orcid.org/0000-0002-2942-4208"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kwan, Wai-Chung","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126603019","display_name":"Rohit Saxena","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Saxena, Rohit","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126657915","display_name":"Ivan Titov","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Titov, Ivan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126630036","display_name":"Pasquale Minervini","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Minervini, Pasquale","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5008920438","display_name":"Emily Allaway","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Allaway, Emily","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.3003999888896942,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.3003999888896942,"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/T10028","display_name":"Topic Modeling","score":0.21119999885559082,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.061900001019239426,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/sql","display_name":"SQL","score":0.5602999925613403},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4196000099182129},{"id":"https://openalex.org/keywords/python","display_name":"Python (programming language)","score":0.4009000062942505},{"id":"https://openalex.org/keywords/automated-reasoning","display_name":"Automated reasoning","score":0.38960000872612},{"id":"https://openalex.org/keywords/cover","display_name":"Cover (algebra)","score":0.3571999967098236}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7896999716758728},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.5726000070571899},{"id":"https://openalex.org/C510870499","wikidata":"https://www.wikidata.org/wiki/Q47607","display_name":"SQL","level":2,"score":0.5602999925613403},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4196000099182129},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.4009000062942505},{"id":"https://openalex.org/C195344581","wikidata":"https://www.wikidata.org/wiki/Q2555318","display_name":"Automated reasoning","level":2,"score":0.38960000872612},{"id":"https://openalex.org/C2780428219","wikidata":"https://www.wikidata.org/wiki/Q16952335","display_name":"Cover (algebra)","level":2,"score":0.3571999967098236},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.35429999232292175},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34869998693466187},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3479999899864197},{"id":"https://openalex.org/C2988963302","wikidata":"https://www.wikidata.org/wiki/Q629206","display_name":"Program code","level":2,"score":0.29319998621940613},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.2644999921321869},{"id":"https://openalex.org/C137287247","wikidata":"https://www.wikidata.org/wiki/Q1329550","display_name":"Static program analysis","level":4,"score":0.2547000050544739}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.17937","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"Article"},{"id":"doi:10.48550/arxiv.2602.17937","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.17937","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2602.17937","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"Article"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.422696590423584,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Instruction":[0],"optimization":[1,31,89],"provides":[2],"a":[3],"lightweight,":[4],"model-agnostic":[5],"approach":[6],"to":[7],"enhancing":[8],"the":[9,20,29,69,97,106],"reasoning":[10,125,137],"performance":[11],"of":[12,24],"large":[13],"language":[14],"models":[15,168],"(LLMs).":[16],"This":[17],"paper":[18],"presents":[19],"first":[21],"systematic":[22],"comparison":[23,133],"instruction":[25,88,176],"optimization,":[26],"based":[27],"on":[28],"DSPy":[30,70],"framework,":[32],"for":[33,101,109,154],"tabular":[34,155],"fact":[35,156],"verification.":[36],"We":[37,64,85],"evaluate":[38],"four":[39,79],"out-of-the-box":[40],"prompting":[41,47,149],"techniques":[42],"that":[43,87,120],"cover":[44],"both":[45],"text-only":[46],"and":[48,59,75,81,103,138],"code":[49],"use:":[50],"direct":[51,124],"prediction,":[52],"Chain-of-Thought":[53],"(CoT),":[54],"ReAct":[55,110,145,163],"with":[56,61,94,159,166],"SQL":[57],"tools,":[58],"CodeAct":[60],"Python":[62],"execution.":[63],"study":[65],"three":[66,82],"optimizers":[67],"from":[68],"framework":[71],"--":[72,77],"COPRO,":[73],"MiPROv2,":[74],"SIMBA":[76,104,121],"across":[78],"benchmarks":[80],"model":[83,115],"families.":[84],"find":[86],"consistently":[90],"improves":[91],"verification":[92],"accuracy,":[93],"MiPROv2":[95],"yielding":[96],"most":[98],"stable":[99],"gains":[100],"CoT,":[102],"providing":[105],"largest":[107],"benefits":[108],"agents,":[111],"particularly":[112],"at":[113],"larger":[114,167],"scales.":[116],"Behavioral":[117],"analyses":[118],"reveal":[119],"encourages":[122],"more":[123],"paths":[126],"by":[127],"applying":[128],"heuristics,":[129],"thereby":[130],"improving":[131],"numerical":[132],"abilities":[134],"in":[135,144],"CoT":[136,151],"helping":[139],"avoid":[140],"unnecessary":[141],"tool":[142],"calls":[143],"agents.":[146],"Across":[147],"different":[148],"techniques,":[150],"remains":[152],"effective":[153],"checking,":[157],"especially":[158],"smaller":[160],"models.":[161],"Although":[162],"agents":[164],"built":[165],"can":[169],"achieve":[170],"competitive":[171],"performance,":[172],"they":[173],"require":[174],"careful":[175],"optimization.":[177]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-02-24T00:00:00"}