{"id":"https://openalex.org/W7137899181","doi":"https://doi.org/10.48550/arxiv.2603.15541","title":"Bridging Local and Global Knowledge: Cascaded Mixture-of-Experts Learning for Near-Shortest Path Routing","display_name":"Bridging Local and Global Knowledge: Cascaded Mixture-of-Experts Learning for Near-Shortest Path Routing","publication_year":2026,"publication_date":"2026-03-16","ids":{"openalex":"https://openalex.org/W7137899181","doi":"https://doi.org/10.48550/arxiv.2603.15541"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.15541","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.15541","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":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.2603.15541","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129685946","display_name":"Yung-Fu Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Yung-Fu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5079903777","display_name":"Anish Arora","orcid":"https://orcid.org/0000-0003-2152-0462"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Arora, Anish","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/T11273","display_name":"Advanced Graph Neural Networks","score":0.7440000176429749,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.7440000176429749,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.07370000332593918,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.035100001841783524,"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/redundancy","display_name":"Redundancy (engineering)","score":0.5715000033378601},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5475000143051147},{"id":"https://openalex.org/keywords/bridging","display_name":"Bridging (networking)","score":0.527899980545044},{"id":"https://openalex.org/keywords/modular-design","display_name":"Modular design","score":0.436599999666214},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.3847000002861023},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.3785000145435333},{"id":"https://openalex.org/keywords/routing","display_name":"Routing (electronic design automation)","score":0.35749998688697815},{"id":"https://openalex.org/keywords/network-topology","display_name":"Network topology","score":0.3544999957084656}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6624000072479248},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.5715000033378601},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5475000143051147},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.527899980545044},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.436599999666214},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.3847000002861023},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3785000145435333},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.35749998688697815},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.3544999957084656},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3513000011444092},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3328999876976013},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.321399986743927},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32010000944137573},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.31940001249313354},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.29739999771118164},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.2883000075817108},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.2865000069141388},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28299999237060547},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.27219998836517334},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.2700999975204468},{"id":"https://openalex.org/C204948658","wikidata":"https://www.wikidata.org/wiki/Q1119410","display_name":"Static routing","level":4,"score":0.26820001006126404},{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.2669000029563904},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.266400009393692},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.2603999972343445},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.25850000977516174},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.25589999556541443}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.15541","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.15541","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":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.2603.15541","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.15541","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.6937938928604126,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"While":[0],"deep":[1],"learning":[2],"models":[3],"that":[4,62,133,157],"leverage":[5],"local":[6,74],"features":[7,75],"have":[8],"demonstrated":[9],"significant":[10],"potential":[11],"for":[12,66],"near-optimal":[13],"routing":[14,53,159],"in":[15,24,166],"dense":[16],"Euclidean":[17],"graphs,":[18],"they":[19],"struggle":[20],"to":[21,46,101,144,164,170],"generalize":[22],"well":[23],"sparse":[25,167],"networks":[26,168],"where":[27],"topological":[28,119],"irregularities":[29],"require":[30],"broader":[31],"structural":[32],"awareness.":[33],"To":[34],"address":[35],"this":[36],"limitation,":[37],"we":[38,127],"train":[39],"a":[40,58,140],"Cascaded":[41],"Mixture":[42],"of":[43,178],"Experts":[44],"(Ca-MoE)":[45],"solve":[47],"the":[48,64,88,95,179],"all-pairs":[49],"near-shortest":[50],"path":[51],"(APNSP)":[52],"problem.":[54],"Our":[55],"Ca-MoE":[56,158],"is":[57,108,124],"modular":[59],"two-tier":[60],"architecture":[61],"supports":[63],"decision-making":[65],"forwarder":[67],"selection":[68],"with":[69],"lower-tier":[70,96],"experts":[71,78,90],"relying":[72,79],"on":[73,80],"and":[76,121,138,173],"upper-tier":[77,89],"global":[81],"features.":[82],"It":[83],"performs":[84],"adaptive":[85],"inference":[86],"wherein":[87],"are":[91,152],"triggered":[92],"only":[93,115],"when":[94,116],"ones":[97],"do":[98],"not":[99],"suffice":[100],"achieve":[102],"adequate":[103],"decision":[104],"quality.":[105],"Computational":[106],"efficiency":[107],"thus":[109],"achieved":[110],"by":[111,118,162],"escalating":[112],"model":[113],"capacity":[114],"necessitated":[117],"complexity,":[120],"parameter":[122],"redundancy":[123],"avoided.":[125],"Furthermore,":[126],"incorporate":[128],"an":[129],"online":[130],"meta-learning":[131],"strategy":[132],"facilitates":[134],"independent":[135],"expert":[136],"fine-tuning":[137],"utilizes":[139],"stability-focused":[141],"update":[142],"mechanism":[143],"prevent":[145],"catastrophic":[146],"forgetting":[147],"as":[148],"new":[149],"graph":[150,185],"environments":[151],"encountered.":[153],"Experimental":[154],"evaluations":[155],"demonstrate":[156],"improves":[160],"accuracy":[161],"up":[163],"29.1%":[165],"compared":[169],"single-expert":[171],"baselines":[172],"maintains":[174],"performance":[175],"within":[176],"1%-6%":[177],"theoretical":[180],"upper":[181],"bound":[182],"across":[183],"diverse":[184],"densities.":[186]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-03-18T00:00:00"}