{"id":"https://openalex.org/W7166694174","doi":"https://doi.org/10.48550/arxiv.2606.28367","title":"Beyond the Reranker: Do RAG Retrieval Enhancements Help Once a Strong Reranker Is Present?","display_name":"Beyond the Reranker: Do RAG Retrieval Enhancements Help Once a Strong Reranker Is Present?","publication_year":2026,"publication_date":"2026-06-14","ids":{"openalex":"https://openalex.org/W7166694174","doi":"https://doi.org/10.48550/arxiv.2606.28367"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.28367","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.28367","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.2606.28367","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103955944","display_name":"Sadanand Singh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Singh, Sadanand","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011561995","display_name":"Allam Reddy","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Reddy, Allam","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5082043200","display_name":"Manan Chopra","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chopra, Manan","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":0.8903999924659729,"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":0.8903999924659729,"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/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.05469999834895134,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.016699999570846558,"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/homogeneous","display_name":"Homogeneous","score":0.7102000117301941},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.6362000107765198},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5845000147819519},{"id":"https://openalex.org/keywords/mean-reciprocal-rank","display_name":"Mean reciprocal rank","score":0.545799970626831},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5394999980926514},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.477400004863739},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.3903000056743622},{"id":"https://openalex.org/keywords/query-expansion","display_name":"Query expansion","score":0.3885999917984009}],"concepts":[{"id":"https://openalex.org/C66882249","wikidata":"https://www.wikidata.org/wiki/Q169336","display_name":"Homogeneous","level":2,"score":0.7102000117301941},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6983000040054321},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.6362000107765198},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5845000147819519},{"id":"https://openalex.org/C44083865","wikidata":"https://www.wikidata.org/wiki/Q3853443","display_name":"Mean reciprocal rank","level":2,"score":0.545799970626831},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5394999980926514},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5267999768257141},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.477400004863739},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.3903000056743622},{"id":"https://openalex.org/C99016210","wikidata":"https://www.wikidata.org/wiki/Q5488129","display_name":"Query expansion","level":2,"score":0.3885999917984009},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.3815000057220459},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.34389999508857727},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.3361000120639801},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32589998841285706},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.32179999351501465},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30219998955726624},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.29089999198913574},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.2881999909877777},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.27059999108314514},{"id":"https://openalex.org/C134121241","wikidata":"https://www.wikidata.org/wiki/Q899301","display_name":"Yield (engineering)","level":2,"score":0.26499998569488525}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.28367","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.28367","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.2606.28367","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.28367","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":[{"display_name":"Quality Education","score":0.8119568824768066,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Retrieval-augmented":[0],"generation":[1],"(RAG)":[2],"is":[3,183],"routinely":[4],"extended":[5],"with":[6,79,90,105],"methods":[7,32,100,127,162],"meant":[8],"to":[9],"improve":[10],"retrieval:":[11],"query":[12,131],"expansion,":[13,19,171],"hierarchical":[14,168],"and":[15,24,58,84,87,92,109,133,151,160,173],"cross-document":[16],"summarization,":[17,169],"graph-based":[18],"per-query":[20],"routing,":[21,172],"rank":[22,174],"fusion,":[23,175],"corrective":[25],"re-retrieval.":[26],"The":[27,157],"benefits":[28],"reported":[29],"for":[30,117,147],"these":[31],"come":[33],"almost":[34],"exclusively":[35],"from":[36],"homogeneous":[37,95],"corpora,":[38],"predominantly":[39],"Wikipedia":[40],"prose.":[41],"Whether":[42],"they":[43],"hold":[44],"on":[45,101,154],"the":[46,120],"mixed-format":[47],"collections":[48],"common":[49,164],"in":[50,163],"practice,":[51],"where":[52],"code,":[53],"markdown,":[54],"tables,":[55],"scientific":[56],"PDFs,":[57],"prose":[59],"are":[60],"interleaved":[61],"within":[62],"one":[63],"corpus,":[64],"has":[65],"not":[66],"been":[67],"measured.":[68],"To":[69],"study":[70],"this":[71],"directly,":[72],"we":[73],"build":[74],"\\textbf{HetDocQA},":[75],"a":[76,102,136,143],"heterogeneous":[77,155],"benchmark":[78],"\\emph{chunker-agnostic}":[80],"span-overlap":[81],"relevance":[82],"labels":[83],"collection-disjoint":[85],"splits,":[86],"pair":[88],"it":[89],"MuSiQue":[91],"QASPER":[93],"as":[94],"controls.":[96],"We":[97],"evaluate":[98],"eight":[99],"shared":[103],"backbone,":[104],"bootstrap":[106],"confidence":[107],"intervals":[108],"multiple-comparison":[110],"correction.":[111],"A":[112],"strong":[113],"cross-encoder":[114],"reranker":[115,182],"accounts":[116],"most":[118],"of":[119],"pipeline's":[121],"quality;":[122],"beyond":[123],"it,":[124],"only":[125,153],"two":[126],"yield":[128],"reliable":[129,178],"gains:":[130],"expansion":[132],"SSCC.":[134],"SSCC,":[135],"per-source":[137],"calibrated":[138],"corrector":[139],"introduced":[140],"here,":[141],"sets":[142],"separate":[144],"acceptance":[145],"threshold":[146],"each":[148],"score":[149],"source":[150],"helps":[152],"data.":[156],"remaining":[158],"reranking":[159],"pool-expansion":[161],"use,":[165],"among":[166],"them":[167],"graph":[170],"give":[176],"no":[177],"gain":[179],"once":[180],"that":[181],"present.":[184]},"counts_by_year":[],"updated_date":"2026-07-01T06:29:00.853634","created_date":"2026-07-01T00:00:00"}
