{"id":"https://openalex.org/W7166189423","doi":"https://doi.org/10.48550/arxiv.2606.27359","title":"When are likely answers right? On Sequence Probability and Correctness in LLMs","display_name":"When are likely answers right? On Sequence Probability and Correctness in LLMs","publication_year":2026,"publication_date":"2026-06-25","ids":{"openalex":"https://openalex.org/W7166189423","doi":"https://doi.org/10.48550/arxiv.2606.27359"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.27359","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.27359","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":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.27359","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5010702746","display_name":"Johannes Zenn","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zenn, Johannes","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139438942","display_name":"Jonas Geiping","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Geiping, Jonas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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/T10028","display_name":"Topic Modeling","score":0.7075999975204468,"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":0.7075999975204468,"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":0.10119999945163727,"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/T13910","display_name":"Computational and Text Analysis Methods","score":0.017899999395012856,"subfield":{"id":"https://openalex.org/subfields/3300","display_name":"General Social Sciences"},"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/decoding-methods","display_name":"Decoding methods","score":0.7476999759674072},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.7368999719619751},{"id":"https://openalex.org/keywords/correctness","display_name":"Correctness","score":0.7021999955177307},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5903000235557556},{"id":"https://openalex.org/keywords/conditional-probability","display_name":"Conditional probability","score":0.5389000177383423},{"id":"https://openalex.org/keywords/probability-mass-function","display_name":"Probability mass function","score":0.414900004863739},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.4050000011920929},{"id":"https://openalex.org/keywords/sequential-decoding","display_name":"Sequential decoding","score":0.35830000042915344}],"concepts":[{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.7476999759674072},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.7368999719619751},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.7021999955177307},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5903000235557556},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5685999989509583},{"id":"https://openalex.org/C44492722","wikidata":"https://www.wikidata.org/wiki/Q327069","display_name":"Conditional probability","level":2,"score":0.5389000177383423},{"id":"https://openalex.org/C197096303","wikidata":"https://www.wikidata.org/wiki/Q869887","display_name":"Probability mass function","level":3,"score":0.414900004863739},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.4050000011920929},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3783999979496002},{"id":"https://openalex.org/C193969084","wikidata":"https://www.wikidata.org/wiki/Q7452500","display_name":"Sequential decoding","level":4,"score":0.35830000042915344},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3560999929904938},{"id":"https://openalex.org/C204397858","wikidata":"https://www.wikidata.org/wiki/Q4437907","display_name":"List decoding","level":5,"score":0.3375999927520752},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.3366999924182892},{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.32710000872612},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.31459999084472656},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.295199990272522},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29260000586509705},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2906000018119812},{"id":"https://openalex.org/C88626702","wikidata":"https://www.wikidata.org/wiki/Q1128903","display_name":"Continuation","level":2,"score":0.28700000047683716},{"id":"https://openalex.org/C40506919","wikidata":"https://www.wikidata.org/wiki/Q7452469","display_name":"Sequence learning","level":2,"score":0.27900001406669617},{"id":"https://openalex.org/C35639132","wikidata":"https://www.wikidata.org/wiki/Q7452468","display_name":"Sequence labeling","level":3,"score":0.25450000166893005}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.27359","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.27359","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.27359","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.27359","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":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Many":[0],"decoding":[1,73,82,129,164],"methods":[2,138],"for":[3,154,177],"large":[4],"language":[5],"models":[6],"can":[7,165],"be":[8,168],"understood":[9],"as":[10],"shifting":[11],"probability":[12,51,108,133,146],"mass":[13],"toward":[14],"outputs":[15],"that":[16,47,105],"are":[17],"more":[18],"likely":[19],"under":[20],"the":[21,26,32,49,100,157],"model,":[22],"either":[23],"locally":[24],"at":[25,31,78],"token":[27],"level":[28],"or":[29,137],"globally":[30],"sequence":[33,45,107,132,145],"level.":[34],"Therefore,":[35],"their":[36],"success":[37],"depends":[38],"on":[39],"a":[40,53,56,87,93,118,149],"fundamental":[41],"question:":[42],"when":[43,163],"does":[44,124,139],"probability,":[46],"is,":[48],"conditional":[50],"of":[52,112,152],"continuation":[54],"given":[55],"prompt,":[57],"actually":[58],"align":[59],"with":[60],"correctness?":[61],"In":[62],"this":[63,70,122],"paper,":[64],"we":[65],"set":[66],"out":[67],"to":[68,99,128,156,170],"quantify":[69],"relationship":[71,123],"across":[72,81,84,89,96,114],"methods,":[74,83],"models,":[75],"and":[76,95,166,173,180],"benchmarks":[77],"four":[79],"levels:":[80],"hyperparameters":[85,136],"within":[86,92,117],"method,":[88],"prompt-answer":[90,115],"pairs":[91,116],"dataset,":[94],"repeated":[97],"responses":[98,155],"same":[101,158],"prompt.":[102,159],"We":[103],"find":[104],"higher":[106],"is":[109,147],"often":[110],"predictive":[111],"correctness":[113,153],"fixed":[119],"dataset.":[120],"However,":[121],"not":[125,140,148],"generally":[126],"transfer":[127],"decisions:":[130],"increasing":[131],"by":[134],"changing":[135],"reliably":[141],"improve":[142,171],"accuracy.":[143],"Further,":[144],"good":[150],"indicator":[151],"These":[160],"findings":[161],"clarify":[162],"cannot":[167],"expected":[169],"correctness,":[172],"provide":[174],"practical":[175],"guidance":[176],"decoding,":[178],"self-consistency,":[179],"verifier-free":[181],"self-improvement.":[182]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-27T00:00:00"}
