{"id":"https://openalex.org/W7118406992","doi":"https://doi.org/10.48550/arxiv.2601.00850","title":"EdgeJury: Cross-Reviewed Small-Model Ensembles for Truthful Question Answering on Serverless Edge Inference","display_name":"EdgeJury: Cross-Reviewed Small-Model Ensembles for Truthful Question Answering on Serverless Edge Inference","publication_year":2025,"publication_date":"2025-12-29","ids":{"openalex":"https://openalex.org/W7118406992","doi":"https://doi.org/10.48550/arxiv.2601.00850"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2601.00850","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.00850","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2601.00850","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5024703234","display_name":"Aayush Kumar","orcid":"https://orcid.org/0009-0001-1048-2352"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Kumar, Aayush","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5024703234"],"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":0.6103000044822693,"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":0.6103000044822693,"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":0.08500000089406967,"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.058400001376867294,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/robustness","display_name":"Robustness (evolution)","score":0.6875},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6078000068664551},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.6033999919891357},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.5884000062942505},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5486000180244446},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.5340999960899353},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.5169000029563904},{"id":"https://openalex.org/keywords/voting","display_name":"Voting","score":0.367000013589859}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7639999985694885},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6875},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6078000068664551},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6033999919891357},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.5884000062942505},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5486000180244446},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.5340999960899353},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.5169000029563904},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4474000036716461},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37689998745918274},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3720000088214874},{"id":"https://openalex.org/C520049643","wikidata":"https://www.wikidata.org/wiki/Q189760","display_name":"Voting","level":3,"score":0.367000013589859},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.3562000095844269},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.34459999203681946},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.33629998564720154},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.3321000039577484},{"id":"https://openalex.org/C118930307","wikidata":"https://www.wikidata.org/wiki/Q600590","display_name":"Tuple","level":2,"score":0.32600000500679016},{"id":"https://openalex.org/C153668964","wikidata":"https://www.wikidata.org/wiki/Q27636","display_name":"Majority rule","level":2,"score":0.32179999351501465},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.31130000948905945},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.28859999775886536},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.27880001068115234},{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.2572000026702881},{"id":"https://openalex.org/C2776831232","wikidata":"https://www.wikidata.org/wiki/Q966812","display_name":"Trusted Computing","level":2,"score":0.2563000023365021}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2601.00850","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.00850","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":"doi:10.48550/arxiv.2601.00850","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.00850","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":"article"},"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":{"Hallucinations":[0],"hinder":[1],"reliable":[2],"question":[3],"answering,":[4],"especially":[5],"in":[6,143],"resource-constrained":[7],"deployments":[8],"where":[9],"frontier-scale":[10],"models":[11,35],"or":[12,178],"retrieval":[13,177],"pipelines":[14],"may":[15],"be":[16],"impractical.":[17],"We":[18],"present":[19],"EdgeJury,":[20],"a":[21,89,94,119],"lightweight":[22],"ensemble":[23],"framework":[24],"that":[25,61,164],"improves":[26],"truthfulness":[27,170],"and":[28,56,70,99,105,114],"robustness":[29],"using":[30],"only":[31],"small":[32],"instruction-tuned":[33],"language":[34],"(3B-8B)":[36],"suitable":[37],"for":[38],"serverless":[39],"edge":[40],"inference.":[41],"EdgeJury":[42,82,124,156],"orchestrates":[43],"four":[44],"stages:":[45],"(1)":[46],"parallel":[47],"role-specialized":[48],"generation,":[49],"(2)":[50],"anonymized":[51],"cross-review":[52],"with":[53],"structured":[54],"critiques":[55],"rankings,":[57],"(3)":[58],"chairman":[59],"synthesis":[60],"integrates":[62],"the":[63,148],"strongest":[64],"content":[65],"while":[66],"addressing":[67],"flagged":[68],"issues,":[69],"(4)":[71],"claim-level":[72],"consistency":[73],"labeling":[74],"based":[75],"on":[76,134,152,171],"inter-model":[77],"agreement.":[78],"On":[79,118],"TruthfulQA":[80],"(MC1),":[81],"achieves":[83,157],"76.2%":[84],"accuracy":[85],"(95%":[86,129],"CI:":[87,130],"72.8-79.6%),":[88],"+21.4%":[90],"relative":[91,127],"improvement":[92],"over":[93],"single":[95],"8B":[96],"baseline":[97],"(62.8%),":[98],"outperforms":[100],"standard":[101],"baselines":[102],"including":[103],"self-consistency":[104],"majority":[106],"voting":[107],"under":[108],"transparent":[109],"compute":[110],"accounting":[111],"(total":[112],"tokens":[113],"platform":[115],"cost":[116],"reported).":[117],"200-question":[120],"adversarial":[121],"EdgeCases":[122],"set,":[123],"yields":[125],"+48.2%":[126],"gains":[128],"44.0-52.4%).":[131],"Manual":[132],"analysis":[133],"100":[135],"incorrect":[136],"answers":[137],"shows":[138],"an":[139],"approximately":[140],"55%":[141],"reduction":[142],"factual":[144],"hallucination":[145],"errors":[146],"versus":[147],"single-model":[149],"baseline.":[150],"Deployed":[151],"Cloudflare":[153],"Workers":[154],"AI,":[155],"8.4":[158],"s":[159],"median":[160],"end-to-end":[161],"latency,":[162],"demonstrating":[163],"coordinated":[165],"small-model":[166],"ensembles":[167],"can":[168],"improve":[169],"misconception-heavy":[172],"QA":[173],"benchmarks":[174],"without":[175],"external":[176],"proprietary":[179],"large-model":[180],"APIs.":[181]},"counts_by_year":[],"updated_date":"2026-01-08T20:10:11.968330","created_date":"2026-01-08T00:00:00"}
