{"id":"https://openalex.org/W7162469461","doi":"https://doi.org/10.48550/arxiv.2605.25394","title":"Second Guess: Detecting Uncertainty Through Abstention and Answer Stability in Small Language Models","display_name":"Second Guess: Detecting Uncertainty Through Abstention and Answer Stability in Small Language Models","publication_year":2026,"publication_date":"2026-05-25","ids":{"openalex":"https://openalex.org/W7162469461","doi":"https://doi.org/10.48550/arxiv.2605.25394"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.25394","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.25394","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.2605.25394","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120696007","display_name":"Ashwath Vaithinathan Aravindan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aravindan, Ashwath Vaithinathan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137056790","display_name":"Mayank Kejriwal","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kejriwal, Mayank","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":0.7745000123977661,"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":0.7745000123977661,"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":0.033900000154972076,"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":0.03290000185370445,"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/key","display_name":"Key (lock)","score":0.588699996471405},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.5745000243186951},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.529699981212616},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.435699999332428},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.3765999972820282},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.3411000072956085}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6557999849319458},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.588699996471405},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.5745000243186951},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.529699981212616},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.435699999332428},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4325999915599823},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.3765999972820282},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36820000410079956},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.3411000072956085},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.3375000059604645},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.31839999556541443},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.301800012588501},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.2800999879837036},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.27730000019073486},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.2646999955177307},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.25870001316070557}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.25394","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.25394","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.2605.25394","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.25394","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":{"Large":[0],"language":[1,21],"models":[2,22,64,76,92,118],"often":[3],"generate":[4],"confident":[5],"but":[6],"incorrect":[7],"answers":[8],"rather":[9],"than":[10],"abstaining":[11],"when":[12,80],"uncertain.":[13],"This":[14],"problem":[15],"is":[16,54,62,86,138],"particularly":[17],"acute":[18],"for":[19,33,46,56,126],"small":[20],"(SLMs),":[23],"where":[24,119],"computational":[25],"constraints":[26],"and":[27,95,123,131],"autonomous":[28],"operation":[29],"amplify":[30],"the":[31,101],"need":[32],"reliable":[34],"uncertainty":[35],"detection.":[36],"We":[37],"propose":[38],"_Second":[39],"Guess_,":[40],"a":[41],"lightweight,":[42],"parameter-free":[43],"prompting":[44],"technique":[45],"abstention":[47],"in":[48,140],"multiple-choice":[49],"question":[50],"answering":[51],"(MCQA)":[52],"that":[53,63],"well-suited":[55],"SLMs.":[57],"Our":[58],"key":[59],"empirical":[60],"insight":[61],"which":[65],"truly":[66],"know":[67],"an":[68,81,111],"answer":[69],"will":[70],"select":[71],"it":[72,109],"consistently,":[73],"while":[74],"uncertain":[75],"exhibit":[77],"unstable":[78],"behavior":[79],"``I":[82],"don't":[83],"know''":[84],"option":[85],"added.":[87],"Evaluated":[88],"on":[89,116],"four":[90,96],"open":[91],"(2B-8B":[93],"parameters)":[94],"benchmarks,":[97],"Second":[98],"Guess":[99],"achieves":[100],"highest":[102],"composite":[103,113],"risk":[104,114],"improvement":[105,115],"of":[106],"10.81\\%.":[107],"Notably,":[108],"maintains":[110],"8\\%":[112],"fine-tuned":[117],"entropy-based":[120],"methods":[121],"degrade,":[122],"improves":[124],"most":[125],"lower-performing":[127],"models.":[128],"All":[129],"code":[130],"results":[132],"required":[133],"to":[134],"reproduce":[135],"this":[136],"work":[137],"available":[139],"https://github.com/Mystic-Slice/second-guess":[141]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-27T00:00:00"}
