{"id":"https://openalex.org/W7164366393","doi":"https://doi.org/10.48550/arxiv.2606.11867","title":"Harnessing Routing Foresight for Micro-step-level MoE load balancing in RL Post-training","display_name":"Harnessing Routing Foresight for Micro-step-level MoE load balancing in RL Post-training","publication_year":2026,"publication_date":"2026-06-10","ids":{"openalex":"https://openalex.org/W7164366393","doi":"https://doi.org/10.48550/arxiv.2606.11867"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.11867","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.11867","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":"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.2606.11867","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138482842","display_name":"Yuming Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Yuming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138469680","display_name":"Haoyang Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Haoyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138396727","display_name":"Sheng Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Sheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138472988","display_name":"Yanfeng Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Yanfeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138470588","display_name":"Tong Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Tong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015552951","display_name":"Xupeng Miao","orcid":"https://orcid.org/0000-0002-9371-8358"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Miao, Xupeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138434274","display_name":"Jie Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Jie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138474622","display_name":"Fangcheng Fu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fu, Fangcheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138422365","display_name":"Bin Cui","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cui, Bin","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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.24789999425411224,"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"}},"topics":[{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.24789999425411224,"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"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.11100000143051147,"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"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.10729999840259552,"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/load-balancing","display_name":"Load balancing (electrical power)","score":0.8205000162124634},{"id":"https://openalex.org/keywords/workload","display_name":"Workload","score":0.6739000082015991},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.6290000081062317},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5576000213623047},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.536899983882904},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.526199996471405},{"id":"https://openalex.org/keywords/routing","display_name":"Routing (electronic design automation)","score":0.4830999970436096}],"concepts":[{"id":"https://openalex.org/C138959212","wikidata":"https://www.wikidata.org/wiki/Q1806783","display_name":"Load balancing (electrical power)","level":3,"score":0.8205000162124634},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7929999828338623},{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.6739000082015991},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.6290000081062317},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5576000213623047},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.536899983882904},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.526199996471405},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.4830999970436096},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.44830000400543213},{"id":"https://openalex.org/C2776999362","wikidata":"https://www.wikidata.org/wiki/Q2349274","display_name":"Planner","level":2,"score":0.3815000057220459},{"id":"https://openalex.org/C2779370713","wikidata":"https://www.wikidata.org/wiki/Q357554","display_name":"Load management","level":2,"score":0.35420000553131104},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.3059999942779541},{"id":"https://openalex.org/C24856439","wikidata":"https://www.wikidata.org/wiki/Q352483","display_name":"Adaptive routing","level":5,"score":0.289000004529953},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.27810001373291016},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C64848388","wikidata":"https://www.wikidata.org/wiki/Q188867","display_name":"Futures studies","level":2,"score":0.2578999996185303},{"id":"https://openalex.org/C58328972","wikidata":"https://www.wikidata.org/wiki/Q184609","display_name":"Expert system","level":2,"score":0.2567000091075897}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.11867","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.11867","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":"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.2606.11867","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.11867","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":"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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Mixture-of-Experts":[0],"(MoE)":[1],"and":[2,139],"reinforcement":[3],"learning":[4],"(RL)":[5],"post-training":[6,161],"now":[7],"dominate":[8],"large":[9],"language":[10],"model":[11],"(LLM)":[12],"development,":[13],"yet":[14],"expert":[15,143],"load":[16,47,61,68,103,123],"imbalance":[17],"remains":[18],"a":[19,66,116,130,155],"critical":[20],"challenge.":[21],"Existing":[22],"load-balancing":[23],"systems":[24],"target":[25],"pre-training":[26],"by":[27,91],"relying":[28,77],"on":[29,78,146],"historical":[30,79],"step-level":[31,46],"statistics.":[32],"However,":[33],"these":[34],"methods":[35],"fail":[36],"under":[37],"the":[38,45,51,83,97,106,121],"unique":[39],"workload":[40],"dynamics":[41],"of":[42,76],"RL":[43,73,85,160],"post-training:":[44],"is":[48],"stable,":[49],"but":[50],"tiny":[52],"batch":[53],"sizes":[54],"processed":[55],"during":[56],"micro-steps":[57],"cause":[58],"severe,":[59],"high-frequency":[60],"fluctuations.":[62],"We":[63],"introduce":[64],"ForeMoE,":[65],"micro-step-level":[67],"balancing":[69,104,124],"system":[70],"for":[71,141],"MoE":[72],"post-training.":[74],"Instead":[75],"statistics,":[80],"ForeMoE":[81,114,151],"exploits":[82],"multi-stage":[84],"pipeline":[86],"(rollout,":[87],"recompute,":[88],"policy":[89],"update)":[90],"using":[92],"foreseeable":[93],"routing":[94],"information":[95],"from":[96],"rollout":[98],"stage":[99],"to":[100,154],"proactively":[101],"guide":[102],"in":[105],"remaining":[107],"stages.":[108],"To":[109],"support":[110],"frequent":[111],"per-micro-step":[112],"reconfiguration,":[113],"employs":[115],"hierarchical":[117],"planner":[118],"that":[119,133,150],"decomposes":[120],"NP-hard":[122],"problem":[125],"into":[126],"tractable":[127],"sub-components,":[128],"alongside":[129],"transfer":[131],"engine":[132],"leverages":[134],"complementary":[135],"hardware":[136],"paths":[137],"(CPU-assisted":[138],"GPU-direct)":[140],"overlapped":[142],"transfer.":[144],"Evaluations":[145],"64":[147],"GPUs":[148],"demonstrate":[149],"achieves":[152],"up":[153],"1.45$\\times$":[156],"speedup":[157],"over":[158],"state-of-the-art":[159],"systems.":[162]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-12T00:00:00"}