{"id":"https://openalex.org/W7127882076","doi":"https://doi.org/10.48550/arxiv.2602.05975","title":"SAGE: Benchmarking and Improving Retrieval for Deep Research Agents","display_name":"SAGE: Benchmarking and Improving Retrieval for Deep Research Agents","publication_year":2026,"publication_date":"2026-02-05","ids":{"openalex":"https://openalex.org/W7127882076","doi":"https://doi.org/10.48550/arxiv.2602.05975"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2602.05975","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.05975","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2602.05975","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5119963925","display_name":"Tiansheng Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Tiansheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125178633","display_name":"Yilun Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Yilun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125170588","display_name":"Canyu Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Canyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122932256","display_name":"Arman Cohan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cohan, Arman","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5125164261","display_name":"Chen Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Chen","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/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.23829999566078186,"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"}},"topics":[{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.23829999566078186,"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/T11948","display_name":"Machine Learning in Materials Science","score":0.17440000176429749,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.11219999939203262,"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/benchmarking","display_name":"Benchmarking","score":0.7807000279426575},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6413999795913696},{"id":"https://openalex.org/keywords/metadata","display_name":"Metadata","score":0.6168000102043152},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4377000033855438},{"id":"https://openalex.org/keywords/data-retrieval","display_name":"Data retrieval","score":0.27549999952316284}],"concepts":[{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.7807000279426575},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7598000168800354},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6413999795913696},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.6168000102043152},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5870000123977661},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4871000051498413},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4401000142097473},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4377000033855438},{"id":"https://openalex.org/C551230270","wikidata":"https://www.wikidata.org/wiki/Q4368942","display_name":"Data retrieval","level":2,"score":0.27549999952316284},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.26649999618530273},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2651999890804291},{"id":"https://openalex.org/C161156560","wikidata":"https://www.wikidata.org/wiki/Q1638872","display_name":"Document retrieval","level":2,"score":0.2623000144958496},{"id":"https://openalex.org/C2781083858","wikidata":"https://www.wikidata.org/wiki/Q17327049","display_name":"Scientific literature","level":2,"score":0.2596000134944916}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2602.05975","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.05975","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2602.05975","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.05975","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Deep":[0],"research":[1,36,68],"agents":[2,69,110],"have":[3,15],"emerged":[4],"as":[5,82,95,108],"powerful":[6],"systems":[7,74],"for":[8,47,137],"addressing":[9],"complex":[10],"queries.":[11],"Meanwhile,":[12],"LLM-based":[13,30,89,103],"retrievers":[14,31,90,104],"demonstrated":[16],"strong":[17],"capability":[18],"in":[19],"following":[20],"instructions":[21],"or":[22],"reasoning.":[23],"This":[24,140],"raises":[25],"a":[26,45,59,119],"critical":[27],"question:":[28],"can":[29],"effectively":[32],"contribute":[33],"to":[34,127],"deep":[35,67],"agent":[37],"workflows?":[38],"To":[39,114],"investigate":[40],"this,":[41],"we":[42,84,117],"introduce":[43],"SAGE,":[44],"benchmark":[46],"scientific":[48,56],"literature":[49],"retrieval":[50,62,135],"comprising":[51],"1,200":[52],"queries":[53],"across":[54],"four":[55],"domains,":[57],"with":[58,76,130],"200,000":[60],"paper":[61],"corpus.":[63],"We":[64],"evaluate":[65],"six":[66],"and":[70,88,93,132,143,148],"find":[71],"that":[72,124],"all":[73],"struggle":[75],"reasoning-intensive":[77],"retrieval.":[78],"Using":[79],"DR":[80],"Tulu":[81],"backbone,":[83],"further":[85],"compare":[86],"BM25":[87,100],"(i.e.,":[91],"ReasonIR":[92],"gte-Qwen2-7B-instruct)":[94],"alternative":[96],"search":[97],"tools.":[98],"Surprisingly,":[99],"significantly":[101],"outperforms":[102],"by":[105],"approximately":[106],"30%,":[107],"existing":[109],"generate":[111],"keyword-oriented":[112],"sub-queries.":[113],"improve":[115],"performance,":[116],"propose":[118],"corpus-level":[120],"test-time":[121],"scaling":[122],"framework":[123],"uses":[125],"LLMs":[126],"augment":[128],"documents":[129],"metadata":[131],"keywords,":[133],"making":[134],"easier":[136],"off-the-shelf":[138],"retrievers.":[139],"yields":[141],"8%":[142],"2%":[144],"gains":[145],"on":[146],"short-form":[147],"open-ended":[149],"questions,":[150],"respectively.":[151]},"counts_by_year":[],"updated_date":"2026-08-16T07:02:28.622633","created_date":"2026-02-07T00:00:00"}
