{"id":"https://openalex.org/W7163915508","doi":"https://doi.org/10.48550/arxiv.2606.07454","title":"PaperFlow: Profiling, Recommending, and Adapting Across Daily Paper Streams","display_name":"PaperFlow: Profiling, Recommending, and Adapting Across Daily Paper Streams","publication_year":2026,"publication_date":"2026-06-05","ids":{"openalex":"https://openalex.org/W7163915508","doi":"https://doi.org/10.48550/arxiv.2606.07454"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.07454","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.07454","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.2606.07454","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138153785","display_name":"Fuqiang Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Fuqiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138104741","display_name":"Song Tan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tan, Song","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111007202","display_name":"Zheng Guo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Zheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138163513","display_name":"Jiaohao Fu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fu, Jiaohao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138114266","display_name":"Xinglong Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Xinglong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138145601","display_name":"Bihui Yu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Bihui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138198324","display_name":"Jie Dong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dong, Jie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138178394","display_name":"Zheng Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Zheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138194635","display_name":"Siyuan Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Siyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138134680","display_name":"Jingxuan Wei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei, Jingxuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5006542157","display_name":"Cheng Tan","orcid":"https://orcid.org/0000-0002-8639-923X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tan, Cheng","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":0.2953999936580658,"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":0.2953999936580658,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.2849999964237213,"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":0.09709999710321426,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.8865000009536743},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.718999981880188},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.5813000202178955},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5719000101089478},{"id":"https://openalex.org/keywords/reading","display_name":"Reading (process)","score":0.525600016117096},{"id":"https://openalex.org/keywords/protocol","display_name":"Protocol (science)","score":0.49889999628067017},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.435699999332428}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.8865000009536743},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7827000021934509},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.718999981880188},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.5813000202178955},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5719000101089478},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.546999990940094},{"id":"https://openalex.org/C554936623","wikidata":"https://www.wikidata.org/wiki/Q199657","display_name":"Reading (process)","level":2,"score":0.525600016117096},{"id":"https://openalex.org/C2780385302","wikidata":"https://www.wikidata.org/wiki/Q367158","display_name":"Protocol (science)","level":3,"score":0.49889999628067017},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4410000145435333},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.435699999332428},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4307999908924103},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42980000376701355},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.428600013256073},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.3327000141143799},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.3301999866962433},{"id":"https://openalex.org/C99016210","wikidata":"https://www.wikidata.org/wiki/Q5488129","display_name":"Query expansion","level":2,"score":0.27730000019073486},{"id":"https://openalex.org/C60777511","wikidata":"https://www.wikidata.org/wiki/Q3045002","display_name":"Concept drift","level":3,"score":0.2703000009059906},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2671999931335449},{"id":"https://openalex.org/C2779532271","wikidata":"https://www.wikidata.org/wiki/Q445558","display_name":"Relevance feedback","level":4,"score":0.2590999901294708},{"id":"https://openalex.org/C42090638","wikidata":"https://www.wikidata.org/wiki/Q4048907","display_name":"STREAMS","level":2,"score":0.2554999887943268}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.07454","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.07454","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.2606.07454","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.07454","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":[{"score":0.7214218378067017,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Scientific":[0],"paper":[1,62,124],"recommendation":[2,156],"is":[3],"typically":[4],"evaluated":[5],"as":[6,19],"static":[7],"ranking":[8],"over":[9],"a":[10,20,34,48,68,92,110,139],"fixed":[11,69],"candidate":[12,100],"set,":[13],"yet":[14],"real":[15],"scientific":[16,155],"reading":[17,172],"unfolds":[18],"daily,":[21],"longitudinal":[22,93],"process":[23],"in":[24],"which":[25,44,58,74],"interests":[26],"shift":[27],"and":[28,46,72,83,104,132,149,174],"feedback":[29,81],"accumulates.":[30],"We":[31,89,136],"introduce":[32],"PaperFlow,":[33],"framework":[35],"that":[36,96,159],"organizes":[37],"it":[38],"into":[39],"three":[40],"coupled":[41],"stages:":[42],"Profiling,":[43],"constructs":[45],"maintains":[47],"structured,":[49],"inspectable":[50],"scholarly":[51],"profile":[52],"from":[53,78],"heterogeneous":[54],"cold-start":[55],"evidence;":[56],"Recommending,":[57],"ranks":[59],"each":[60],"date-specific":[61],"stream":[63],"through":[64],"multi-signal":[65],"aggregation":[66],"under":[67,109],"display":[70],"budget;":[71],"Adapting,":[73],"updates":[75],"user":[76],"state":[77],"semantically":[79],"distinct":[80],"signals":[82],"models":[84],"interest":[85],"drift":[86],"across":[87],"days.":[88],"further":[90],"define":[91],"user-day":[94,127],"benchmark":[95,116],"fixes":[97],"users,":[98,121],"dates,":[99],"pools,":[101],"visible":[102],"inputs,":[103],"hidden":[105],"simulated":[106,119,171],"relevance":[107],"labels":[108],"shared":[111],"temporal":[112],"information":[113],"boundary.":[114],"The":[115],"contains":[117],"24":[118],"research":[120],"50":[122],"daily":[123],"streams,":[125],"1,200":[126],"episodes,":[128],"20,727":[129],"unique":[130],"papers,":[131],"497,448":[133],"episode-paper":[134],"records.":[135],"additionally":[137],"specify":[138],"blind":[140,177],"human-evaluation":[141,178],"protocol":[142],"to":[143],"validate":[144],"alignment":[145,169],"between":[146],"automatic":[147],"metrics":[148],"expert":[150],"judgments.":[151],"Experiments":[152],"against":[153],"five":[154],"baselines":[157],"show":[158],"PaperFlow":[160],"achieves":[161],"the":[162,166,175],"strongest":[163],"oracle-based":[164],"ranking,":[165],"highest":[167],"behavioral":[168],"with":[170],"selections,":[173],"best":[176],"score.":[179]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-09T00:00:00"}
