{"id":"https://openalex.org/W7160933792","doi":"https://doi.org/10.48550/arxiv.2605.09023","title":"Using Semantic Distance to Estimate Uncertainty in LLM-Based Code Generation","display_name":"Using Semantic Distance to Estimate Uncertainty in LLM-Based Code Generation","publication_year":2026,"publication_date":"2026-05-09","ids":{"openalex":"https://openalex.org/W7160933792","doi":"https://doi.org/10.48550/arxiv.2605.09023"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.09023","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.09023","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":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.2605.09023","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135915951","display_name":"Weilin He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Weilin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135972999","display_name":"Arindam Sharma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sharma, Arindam","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135918656","display_name":"Cristina David","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"David, Cristina","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/T10260","display_name":"Software Engineering Research","score":0.5878999829292297,"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"}},"topics":[{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":0.5878999829292297,"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/T10743","display_name":"Software Testing and Debugging Techniques","score":0.1476999968290329,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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/T10126","display_name":"Logic, programming, and type systems","score":0.11209999769926071,"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/correctness","display_name":"Correctness","score":0.7355999946594238},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.659500002861023},{"id":"https://openalex.org/keywords/java","display_name":"Java","score":0.5504000186920166},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.48030000925064087},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4523000121116638},{"id":"https://openalex.org/keywords/fuzz-testing","display_name":"Fuzz testing","score":0.412200003862381}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7569000124931335},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.7355999946594238},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.659500002861023},{"id":"https://openalex.org/C548217200","wikidata":"https://www.wikidata.org/wiki/Q251","display_name":"Java","level":2,"score":0.5504000186920166},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.48030000925064087},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.45249998569488525},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4523000121116638},{"id":"https://openalex.org/C111065885","wikidata":"https://www.wikidata.org/wiki/Q1189053","display_name":"Fuzz testing","level":3,"score":0.412200003862381},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.35030001401901245},{"id":"https://openalex.org/C58642233","wikidata":"https://www.wikidata.org/wiki/Q8269924","display_name":"Taxonomy (biology)","level":2,"score":0.3361000120639801},{"id":"https://openalex.org/C75373757","wikidata":"https://www.wikidata.org/wiki/Q7410160","display_name":"Sampling design","level":3,"score":0.31610000133514404},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.31529998779296875},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3019999861717224},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.301800012588501},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2752000093460083},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.25619998574256897},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.2517000138759613}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.09023","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.09023","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.09023","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.09023","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":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"LLMs":[0],"show":[1],"strong":[2,97],"performance":[3],"in":[4],"code":[5],"generation,":[6],"but":[7,76],"their":[8,25,79],"outputs":[9],"lack":[10],"correctness":[11],"guarantees.":[12],"Sample-based":[13],"uncertainty":[14,66],"estimators":[15,29],"address":[16],"this":[17],"by":[18,147],"generating":[19],"multiple":[20],"candidate":[21],"programs":[22,74],"and":[23,41,58,87,92,101,117,141,144],"measuring":[24],"disagreement.":[26],"However,":[27],"existing":[28,152],"make":[30],"different":[31],"design":[32,62],"choices":[33,57],"about":[34],"how":[35,77],"behaviours":[36,81],"are":[37],"identified,":[38],"aggregated,":[39],"referenced":[40],"compared,":[42],"making":[43],"them":[44],"difficult":[45],"to":[46,151],"assess.":[47],"We":[48],"therefore":[49],"first":[50],"introduce":[51],"a":[52,60],"taxonomy":[53],"that":[54],"disentangles":[55],"these":[56],"reveals":[59],"missing":[61],"point:":[63],"semantic":[64],"distance-aware":[65],"estimation,":[67],"which":[68],"measures":[69],"not":[70],"only":[71],"whether":[72],"sampled":[73],"disagree,":[75],"severely":[78],"execution":[80],"differ.":[82],"Across":[83],"LiveCodeBench,":[84],"MBPP,":[85],"HumanEval-X":[86],"BigCodeBench,":[88],"spanning":[89],"Python,":[90],"Java":[91],"C++,":[93],"our":[94],"metrics":[95],"provide":[96],"proxies":[98],"for":[99],"correctness,":[100],"consistently":[102],"outperform":[103],"state-of-the-art":[104],"sample-based":[105],"baselines":[106],"across":[107,136],"both":[108],"closed-source":[109],"models":[110],"(GPT-3.5-Turbo,":[111],"GPT-4o-mini,":[112],"Gemini-2.5-Flash-Lite,":[113],"Claude":[114],"Opus":[115],"4.5)":[116],"an":[118],"open-source":[119],"model":[120,129],"(DeepSeek-Coder-V2).":[121],"The":[122],"method":[123],"is":[124],"practical:":[125],"it":[126],"requires":[127],"neither":[128],"internals":[130],"nor":[131],"LLM-as-judge":[132],"calls,":[133],"remains":[134],"robust":[135],"models,":[137],"languages,":[138],"sampling":[139],"temperatures":[140],"fuzzing":[142],"settings,":[143],"reduces":[145],"runtime":[146],"approximately":[148],"48-79%":[149],"relative":[150],"baselines.":[153]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-13T00:00:00"}