{"id":"https://openalex.org/W7154140744","doi":"https://doi.org/10.48550/arxiv.2604.09107","title":"TensorHub: Scalable and Elastic Weight Transfer for LLM RL Training","display_name":"TensorHub: Scalable and Elastic Weight Transfer for LLM RL Training","publication_year":2026,"publication_date":"2026-04-10","ids":{"openalex":"https://openalex.org/W7154140744","doi":"https://doi.org/10.48550/arxiv.2604.09107"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.09107","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.09107","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.09107","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133530341","display_name":"Chenhao Ye","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ye, Chenhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133502989","display_name":"Huaizheng Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Huaizheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030930550","display_name":"Mingcong Han","orcid":"https://orcid.org/0009-0008-1536-7485"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han, Mingcong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037661446","display_name":"Baoquan Zhong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhong, Baoquan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133527436","display_name":"Xiang LiuXing Li","orcid":"https://orcid.org/0009-0006-2113-0586"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Xiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133520184","display_name":"Qixiang Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Qixiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133496514","display_name":"Xinyi Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Xinyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133512467","display_name":"Weidong Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Weidong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133485451","display_name":"Kaihua Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Kaihua","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133542084","display_name":"Wang Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Wang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133518805","display_name":"He Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, He","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086945155","display_name":"Wencong Xiao","orcid":"https://orcid.org/0000-0002-3043-522X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiao, Wencong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133541792","display_name":"Andrea C. Arpaci-Dusseau","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Arpaci-Dusseau, Andrea C.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133491573","display_name":"Remzi H. Arpaci-Dusseau","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Arpaci-Dusseau, Remzi H.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":14,"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/T10714","display_name":"Software-Defined Networks and 5G","score":0.14110000431537628,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10714","display_name":"Software-Defined Networks and 5G","score":0.14110000431537628,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.11020000278949738,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.08950000256299973,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/scalability","display_name":"Scalability","score":0.6996999979019165},{"id":"https://openalex.org/keywords/fault-tolerance","display_name":"Fault tolerance","score":0.4814999997615814},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.46790000796318054},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.44850000739097595},{"id":"https://openalex.org/keywords/transfer","display_name":"Transfer (computing)","score":0.4325999915599823},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.3776000142097473},{"id":"https://openalex.org/keywords/abstraction","display_name":"Abstraction","score":0.37049999833106995},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.3603000044822693},{"id":"https://openalex.org/keywords/stall","display_name":"Stall (fluid mechanics)","score":0.3407000005245209}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7728999853134155},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6996999979019165},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.5162000060081482},{"id":"https://openalex.org/C63540848","wikidata":"https://www.wikidata.org/wiki/Q3140932","display_name":"Fault tolerance","level":2,"score":0.4814999997615814},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.46790000796318054},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.44850000739097595},{"id":"https://openalex.org/C2776175482","wikidata":"https://www.wikidata.org/wiki/Q1195816","display_name":"Transfer (computing)","level":2,"score":0.4325999915599823},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.3776000142097473},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.37049999833106995},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.3603000044822693},{"id":"https://openalex.org/C5804382","wikidata":"https://www.wikidata.org/wiki/Q752034","display_name":"Stall (fluid mechanics)","level":2,"score":0.3407000005245209},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3222000002861023},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.3174000084400177},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.30970001220703125},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.29760000109672546},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.2930999994277954},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.29159998893737793},{"id":"https://openalex.org/C557945733","wikidata":"https://www.wikidata.org/wiki/Q389772","display_name":"Data transmission","level":2,"score":0.2915000021457672},{"id":"https://openalex.org/C138959212","wikidata":"https://www.wikidata.org/wiki/Q1806783","display_name":"Load balancing (electrical power)","level":3,"score":0.288100004196167},{"id":"https://openalex.org/C193702766","wikidata":"https://www.wikidata.org/wiki/Q1414548","display_name":"Concurrency","level":2,"score":0.28540000319480896},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.28110000491142273},{"id":"https://openalex.org/C459310","wikidata":"https://www.wikidata.org/wiki/Q117801","display_name":"Computational science","level":1,"score":0.2793000042438507},{"id":"https://openalex.org/C147358964","wikidata":"https://www.wikidata.org/wiki/Q1200992","display_name":"Abstraction layer","level":3,"score":0.2768000066280365},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.27070000767707825},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.25859999656677246},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.2578999996185303},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.25450000166893005},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.2533000111579895}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.09107","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.09107","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.09107","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.09107","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":"article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.4279152452945709,"display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Modern":[0],"LLM":[1],"reinforcement":[2],"learning":[3],"(RL)":[4],"workloads":[5,151],"require":[6],"a":[7,49,121],"highly":[8,60],"efficient":[9],"weight":[10,22,55,171],"transfer":[11,23,56],"system":[12,123],"to":[13,27,115,147,165,192],"scale":[14],"training":[15],"across":[16],"heterogeneous":[17],"computational":[18],"resources.":[19],"However,":[20],"existing":[21],"approaches":[24],"either":[25],"fail":[26],"provide":[28],"flexibility":[29],"for":[30,53,107,167,173],"dynamically":[31],"scaling":[32],"clusters":[33],"or":[34],"incur":[35],"fundamental":[36],"data":[37],"movement":[38],"overhead,":[39],"resulting":[40],"in":[41,64,190],"poor":[42],"performance.":[43],"We":[44,118],"introduce":[45],"Reference-Oriented":[46],"Storage":[47],"(ROS),":[48],"new":[50],"storage":[51],"abstraction":[52],"RL":[54,195],"that":[57,70,101,124,139],"exploits":[58],"the":[59,68,74,94,99,126],"replicated":[61],"model":[62,75],"weights":[63,76,104],"place.":[65],"ROS":[66,86,111,127],"presents":[67],"illusion":[69],"certain":[71],"versions":[72],"of":[73,93],"are":[77],"stored":[78],"and":[79,134,145,178],"can":[80],"be":[81],"fetched":[82],"on":[83,105],"demand.":[84],"Underneath,":[85],"does":[87],"not":[88],"physically":[89],"store":[90],"any":[91],"copies":[92],"weights;":[95],"instead,":[96],"it":[97],"tracks":[98],"workers":[100],"hold":[102],"these":[103],"GPUs":[106],"inference.":[108],"Upon":[109],"request,":[110],"directly":[112],"uses":[113],"them":[114],"serve":[116],"reads.":[117],"build":[119],"TensorHub,":[120],"production-quality":[122],"extends":[125],"idea":[128],"with":[129,152],"topology-optimized":[130],"transfer,":[131],"strong":[132],"consistency,":[133],"fault":[135],"tolerance.":[136],"Evaluation":[137],"shows":[138],"TensorHub":[140,157,186],"fully":[141],"saturates":[142],"RDMA":[143],"bandwidth":[144],"adapts":[146],"three":[148],"distinct":[149],"rollout":[150,175,181],"minimal":[153],"engineering":[154],"effort.":[155],"Specifically,":[156],"reduces":[158],"total":[159],"GPU":[160],"stall":[161,182],"time":[162,183],"by":[163,176,184],"up":[164],"6.7x":[166],"standalone":[168],"rollouts,":[169],"accelerates":[170],"update":[172],"elastic":[174],"4.8x,":[177],"cuts":[179],"cross-datacenter":[180],"19x.":[185],"has":[187],"been":[188],"deployed":[189],"production":[191],"support":[193],"cutting-edge":[194],"training.":[196]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-14T00:00:00"}