{"id":"https://openalex.org/W7162393605","doi":"https://doi.org/10.48550/arxiv.2605.25382","title":"AuthTrace: Diagnosing Evidence Construction in Thematically Dense Single-Author Corpora","display_name":"AuthTrace: Diagnosing Evidence Construction in Thematically Dense Single-Author Corpora","publication_year":2026,"publication_date":"2026-05-25","ids":{"openalex":"https://openalex.org/W7162393605","doi":"https://doi.org/10.48550/arxiv.2605.25382"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.25382","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.25382","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.2605.25382","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5108883637","display_name":"Wu Xiaoqing","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Xiaoqing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137021923","display_name":"Feifei Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Feifei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093951156","display_name":"\u94ed\u8c6a \u6881","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ming, Haoliang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5053614230","display_name":"Wenhui Que","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Que, Wenhui","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":0.5120000243186951,"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":0.5120000243186951,"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":0.10140000283718109,"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"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.03689999878406525,"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/set","display_name":"Set (abstract data type)","score":0.6129000186920166},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5238000154495239},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5146999955177307},{"id":"https://openalex.org/keywords/text-corpus","display_name":"Text corpus","score":0.41850000619888306},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.41530001163482666},{"id":"https://openalex.org/keywords/corpus-linguistics","display_name":"Corpus linguistics","score":0.38029998540878296},{"id":"https://openalex.org/keywords/simplicity","display_name":"Simplicity","score":0.36719998717308044}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7272999882698059},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6668000221252441},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6129000186920166},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5733000040054321},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5238000154495239},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5146999955177307},{"id":"https://openalex.org/C2474386","wikidata":"https://www.wikidata.org/wiki/Q461183","display_name":"Text corpus","level":2,"score":0.41850000619888306},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.41530001163482666},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.38339999318122864},{"id":"https://openalex.org/C532629269","wikidata":"https://www.wikidata.org/wiki/Q865083","display_name":"Corpus linguistics","level":2,"score":0.38029998540878296},{"id":"https://openalex.org/C2776372474","wikidata":"https://www.wikidata.org/wiki/Q508291","display_name":"Simplicity","level":2,"score":0.36719998717308044},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.349700003862381},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3208000063896179},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.29919999837875366},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.2955000102519989},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.2928999960422516},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.2720000147819519}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.25382","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.25382","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.2605.25382","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.25382","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":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.47808682918548584}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Evidence":[0],"construction--the":[1],"stage":[2],"that":[3,114],"determines":[4],"which":[5,26,177],"passages":[6],"reach":[7],"the":[8,54,88,91,118,126],"language":[9],"model":[10],"before":[11],"generation":[12],"begins--is":[13],"evaluated":[14],"paradigm":[15,178],"by":[16],"paradigm,":[17],"leaving":[18],"practitioners":[19],"with":[20,53],"no":[21],"principled":[22],"way":[23],"to":[24,86,164],"diagnose":[25],"organization":[27],"strategy":[28],"fails,":[29],"where,":[30],"or":[31],"why.":[32],"We":[33],"introduce":[34],"AuthTrace,":[35],"a":[36,66,166,181],"diagnostic":[37,93,168],"benchmark":[38],"built":[39],"on":[40],"thematically":[41,155],"dense":[42],"single-author":[43],"corpora":[44],"where":[45,172],"near-miss":[46],"distractors":[47],"share":[48],"style,":[49],"topic,":[50],"and":[51,65,75,102,176],"vocabulary":[52],"required":[55,85],"evidence.":[56],"AuthTrace":[57],"provides":[58],"explicit":[59],"quoted":[60],"evidence,":[61],"exact":[62],"fan-in":[63,79,162],"annotation,":[64],"unified":[67],"pack-level":[68],"protocol":[69],"measuring":[70],"evidence":[71,73,115,138,157],"recall,":[72],"precision,":[74],"answer":[76,123,141],"correctness.":[77],"A":[78],"gradient--the":[80],"number":[81],"of":[82,122],"source":[83],"documents":[84],"support":[87],"answer--serves":[89],"as":[90],"primary":[92,127],"axis,":[94],"enabling":[95],"controlled":[96],"comparison":[97],"across":[98,108],"retrieval,":[99],"memory,":[100],"graph,":[101],"structured-evidence":[103],"paradigms.":[104],"Evaluating":[105],"eight":[106],"systems":[107,174],"two":[109],"QA":[110],"models,":[111],"we":[112],"find":[113],"recall":[116],"is":[117],"strongest":[119],"observed":[120],"predictor":[121],"correctness":[124],"under":[125],"reader-judge":[128],"pair":[129],"(r":[130],"=":[131],"0.96);":[132],"most":[133],"failures":[134],"stem":[135],"from":[136],"missing":[137],"rather":[139],"than":[140,154],"synthesis.":[142],"Fan-in":[143],"further":[144],"exposes":[145],"paradigm-specific":[146],"collapse":[147],"patterns:":[148],"flat":[149],"retrieval":[150],"degrades":[151],"2-3x":[152],"faster":[153],"organized":[156],"construction.":[158],"These":[159],"results":[160],"show":[161],"decomposition":[163],"be":[165],"reusable":[167],"lens":[169],"for":[170],"identifying":[171],"evidence-construction":[173],"fail":[175],"best":[179],"serves":[180],"given":[182],"workload.":[183]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-27T00:00:00"}