{"id":"https://openalex.org/W7224964291","doi":"https://doi.org/10.48550/arxiv.2610.39188","title":"Read More, Reason Deeper: Latent Workspaces for Long-Sequence Recommendation","display_name":"Read More, Reason Deeper: Latent Workspaces for Long-Sequence Recommendation","publication_year":2026,"publication_date":"2026-10-29","ids":{"openalex":"https://openalex.org/W7224964291","doi":"https://doi.org/10.48550/arxiv.2610.39188"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2610.39188","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.39188","pdf_url":"https://arxiv.org/pdf/2610.39188","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,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2610.39188","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5009874448","display_name":"Renzhi Wu","orcid":"https://orcid.org/0000-0002-9144-8999","observed_orcids":["https://orcid.org/0000-0002-9144-8999"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Renzhi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160185661","display_name":"Li Sheng","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sheng, Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160210585","display_name":"Zikun Cui","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cui, Zikun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160178239","display_name":"Junjie Yang","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Junjie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125421069","display_name":"Tai Guo","orcid":"https://orcid.org/0009-0002-1864-9468","observed_orcids":["https://orcid.org/0009-0002-1864-9468"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Tai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033904846","display_name":"Keke Zhai","orcid":"https://orcid.org/0000-0002-5240-8011","observed_orcids":["https://orcid.org/0000-0002-5240-8011"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhai, Keke","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160151538","display_name":"Yan Li","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5151996985","display_name":"Jerry Fu","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fu, Jerry","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005356160","display_name":"Nipun Mathur","orcid":"https://orcid.org/0009-0007-1175-4931","observed_orcids":["https://orcid.org/0009-0007-1175-4931"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mathur, Nipun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108942109","display_name":"Sri Reddy","orcid":"https://orcid.org/0009-0001-1504-9013","observed_orcids":["https://orcid.org/0009-0001-1504-9013"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Reddy, Sri","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5160181541","display_name":"Hong Li","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Hong","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":true,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9990000128746033,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9990000128746033,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.0007999999797903001,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/reasoning-depth","display_name":"reasoning depth","score":0.9210000038146973},{"id":"https://openalex.org/keywords/computational-efficiency","display_name":"computational efficiency","score":0.42500001192092896}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7730000019073486},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.5949000120162964},{"id":"https://openalex.org/C58581272","wikidata":"https://www.wikidata.org/wiki/Q12741163","display_name":"Workspace","level":3,"score":0.5490999817848206},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5422999858856201},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.5239999890327454},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5202999711036682},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.519599974155426},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5152000188827515},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.41850000619888306},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4142000079154968},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41350001096725464},{"id":"https://openalex.org/C554936623","wikidata":"https://www.wikidata.org/wiki/Q199657","display_name":"Reading (process)","level":2,"score":0.36730000376701355},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3587000072002411},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.3573000133037567},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.3555999994277954},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.3366999924182892},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.33379998803138733},{"id":"https://openalex.org/C136643341","wikidata":"https://www.wikidata.org/wiki/Q1361526","display_name":"Reachability","level":2,"score":0.3109999895095825},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.3082999885082245},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.301800012588501},{"id":"https://openalex.org/C20162079","wikidata":"https://www.wikidata.org/wiki/Q1151406","display_name":"Case-based reasoning","level":2,"score":0.2921999990940094},{"id":"https://openalex.org/C166052673","wikidata":"https://www.wikidata.org/wiki/Q83021","display_name":"Empirical evidence","level":2,"score":0.27959999442100525},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2639000117778778},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.2619999945163727}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2610.39188","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.39188","pdf_url":"https://arxiv.org/pdf/2610.39188","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,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2610.39188","doi":"https://doi.org/10.48550/arxiv.2610.39188","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2610.39188","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,"listed_in":[],"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"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2610.39188","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.39188","pdf_url":"https://arxiv.org/pdf/2610.39188","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,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7224964291.pdf","grobid_xml":"https://content.openalex.org/works/W7224964291.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7118827344","https://openalex.org/W7168387893","https://openalex.org/W7211995518","https://openalex.org/W7104905479","https://openalex.org/W7203894965","https://openalex.org/W7168312631","https://openalex.org/W4417466219","https://openalex.org/W7128614083","https://openalex.org/W7128777592","https://openalex.org/W4416453563"],"abstract_inverted_index":{"Long-sequence":[0],"recommendation":[1],"can":[2],"improve":[3],"along":[4],"two":[5,165],"axes:":[6],"\\emph{evidence":[7],"scaling}":[8,14],"exposes":[9],"longer":[10],"histories,":[11,120],"while":[12,153],"\\emph{reasoning":[13],"adds":[15],"layers":[16,41],"that":[17,19,172],"interpret":[18],"evidence":[20,56,98,175],"for":[21],"a":[22,62],"candidate.":[23],"Existing":[24],"models":[25],"couple":[26],"them:":[27],"sequence":[28],"encoders":[29],"propagate":[30],"every":[31],"added":[32],"event":[33],"through":[34],"depth,":[35,102],"whereas":[36],"one-shot":[37],"selection":[38],"prevents":[39],"later":[40],"from":[42,71,176],"revisiting":[43],"omitted":[44],"evidence.":[45],"We":[46,89],"introduce":[47],"the":[48,69,135,140],"Latent":[49],"Workspace":[50],"Ranker":[51],"(LWR),":[52],"which":[53],"keeps":[54],"typed":[55],"in":[57],"persistent":[58],"banks":[59,70],"and":[60,75,83,109,126,182,187],"propagates":[61],"fixed-size":[63],"candidate-local":[64],"workspace.":[65],"Each":[66],"layer":[67],"rereads":[68],"its":[72],"evolving":[73],"workspace":[74],"archives":[76],"compact":[77],"post-interaction":[78],"state,":[79],"allowing":[80],"history":[81],"length":[82],"reasoning":[84,103,124,183],"depth":[85],"to":[86],"grow":[87],"independently.":[88],"compare":[90],"four":[91],"architectures":[92],"across":[93],"various":[94],"history--depth":[95],"configurations":[96],"using":[97,154],"scaling":[99,104],"at":[100,105,118,134],"fixed":[101,106],"10K":[107,144],"history,":[108,145],"their":[110],"joint":[111,141],"compute-efficient":[112],"frontier.":[113,142],"LWR":[114],"leads":[115],"all":[116],"families":[117],"long":[119],"continues":[121],"improving":[122],"with":[123],"compute,":[125],"converts":[127],"additional":[128],"training":[129],"compute":[130],"into":[131],"quality":[132],"gains":[133],"fastest":[136],"fitted":[137],"rate":[138],"on":[139,164],"At":[143],"it":[146],"improves":[147],"NE":[148],"by":[149],"0.19%":[150],"over":[151],"HSTU":[152],"69.6%":[155],"fewer":[156],"forward":[157],"GFLOP/request.":[158],"It":[159],"also":[160],"outperforms":[161],"existing":[162],"baselines":[163],"billion-scale":[166],"ranking":[167],"surfaces.":[168],"These":[169],"results":[170],"show":[171],"separating":[173],"addressable":[174],"propagated":[177],"state":[178],"makes":[179],"reading":[180],"more":[181],"deeper":[184],"independently":[185],"controllable":[186],"jointly":[188],"useful.":[189]},"counts_by_year":[],"updated_date":"2026-11-02T09:45:03.842371","created_date":"2026-10-31T00:00:00"}
