{"id":"https://openalex.org/W7163384323","doi":"https://doi.org/10.48550/arxiv.2606.03535","title":"Can LLM Rerankers Predict Their Own Ranking Performance?","display_name":"Can LLM Rerankers Predict Their Own Ranking Performance?","publication_year":2026,"publication_date":"2026-06-02","ids":{"openalex":"https://openalex.org/W7163384323","doi":"https://doi.org/10.48550/arxiv.2606.03535"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.03535","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.03535","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.2606.03535","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137790671","display_name":"Shiyu Ni","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ni, Shiyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137729419","display_name":"Keping Bi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bi, Keping","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137736330","display_name":"Jiafeng Guo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Jiafeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137773576","display_name":"Jingtong Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Jingtong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025404139","display_name":"Zengxin Han","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han, Zengxin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137778870","display_name":"Xueqi Cheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cheng, Xueqi","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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.8569999933242798,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.8569999933242798,"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/T13274","display_name":"Expert finding and Q&A systems","score":0.03869999945163727,"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/T10028","display_name":"Topic Modeling","score":0.013000000268220901,"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/ranking","display_name":"Ranking (information retrieval)","score":0.836899995803833},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.6852999925613403},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5950000286102295},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.37299999594688416},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.36410000920295715},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.35350000858306885}],"concepts":[{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.836899995803833},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.6852999925613403},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6664999723434448},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5950000286102295},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5637000203132629},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5378999710083008},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.37299999594688416},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.36410000920295715},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.35350000858306885},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.32690000534057617},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.30640000104904175},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.3003999888896942},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2793000042438507},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2535000145435333}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.03535","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.03535","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.2606.03535","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.03535","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":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.4843010902404785}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Retrieval":[0],"effectiveness":[1],"varies":[2],"substantially":[3],"across":[4,72],"queries,":[5],"making":[6],"it":[7,54],"important":[8],"to":[9,132],"estimate":[10,48],"ranking":[11,53],"quality":[12,50],"before":[13],"relevance":[14],"judgments":[15],"are":[16],"available.":[17],"Query":[18],"performance":[19],"prediction":[20],"(QPP)":[21],"addresses":[22],"this":[23,38],"need,":[24],"but":[25],"most":[26],"existing":[27],"methods":[28],"rely":[29],"on":[30,84],"external":[31],"predictors":[32],"after":[33],"retrieval":[34],"or":[35],"reranking.":[36],"In":[37],"paper,":[39],"we":[40,68,120],"study":[41],"\\textit{reranker-internal":[42],"QPP}:":[43],"can":[44],"an":[45],"LLM":[46,130],"reranker":[47],"the":[49,52,81,98],"of":[51],"has":[55],"just":[56],"produced?":[57],"We":[58],"investigate":[59],"both":[60],"training-free":[61,66],"and":[62,75,102,126],"training-based":[63],"approaches.":[64],"For":[65],"estimation,":[67],"examine":[69],"metric-specific":[70],"self-consistency":[71,94],"sampled":[73],"rankings":[74],"verbalized":[76,111,118],"confidence":[77,112],"produced":[78],"directly":[79],"by":[80],"reranker.":[82],"Experiments":[83],"TREC":[85],"Deep":[86],"Learning":[87],"2019--2022":[88],"with":[89,97,137],"four":[90],"LLMs":[91],"show":[92],"that":[93],"is":[95,113],"competitive":[96],"state-of-the-art":[99],"(SOTA)":[100],"approach":[101],"better":[103],"calibrated":[104,134],"in":[105],"almost":[106],"all":[107],"settings,":[108],"while":[109],"direct":[110],"severely":[114],"overconfident.":[115],"To":[116],"improve":[117],"confidence,":[119],"propose":[121],"two":[122],"supervised":[123],"methods,":[124],"Verb-Num":[125],"Verb-List,":[127],"which":[128],"enable":[129],"rerankers":[131],"produce":[133],"ranking-quality":[135],"estimates":[136],"only":[138],"a":[139],"few":[140],"additional":[141],"output":[142],"tokens.":[143]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-04T00:00:00"}
