{"id":"https://openalex.org/W7140721714","doi":"https://doi.org/10.48550/arxiv.2603.23975","title":"HyDRA: Hybrid Domain-Aware Robust Architecture for Heterogeneous Collaborative Perception","display_name":"HyDRA: Hybrid Domain-Aware Robust Architecture for Heterogeneous Collaborative Perception","publication_year":2026,"publication_date":"2026-03-25","ids":{"openalex":"https://openalex.org/W7140721714","doi":"https://doi.org/10.48550/arxiv.2603.23975"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.23975","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.23975","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.2603.23975","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130632639","display_name":"Minwoo Song","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Minwoo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130703335","display_name":"Minhee Kang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kang, Minhee","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5130647202","display_name":"Heejin Ahn","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ahn, Heejin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.14139999449253082,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.14139999449253082,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10709","display_name":"Social Robot Interaction and HRI","score":0.12849999964237213,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.12240000069141388,"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/classifier","display_name":"Classifier (UML)","score":0.5706999897956848},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.5450000166893005},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.515500009059906},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.46050000190734863},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.43290001153945923},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4165000021457672},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.4050000011920929},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.3799999952316284},{"id":"https://openalex.org/keywords/end-to-end-principle","display_name":"End-to-end principle","score":0.3587999939918518}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.814300000667572},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5706999897956848},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5655999779701233},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5450000166893005},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.5360000133514404},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.515500009059906},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.46050000190734863},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43470001220703125},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.43290001153945923},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4165000021457672},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.4050000011920929},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.3799999952316284},{"id":"https://openalex.org/C74296488","wikidata":"https://www.wikidata.org/wiki/Q2527392","display_name":"End-to-end principle","level":2,"score":0.3587999939918518},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3531000018119812},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.3488999903202057},{"id":"https://openalex.org/C2780735816","wikidata":"https://www.wikidata.org/wiki/Q28324931","display_name":"Incremental learning","level":2,"score":0.313400000333786},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.3131999969482422},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3102000057697296},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.3034999966621399},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.29840001463890076},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2849000096321106},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.27950000762939453},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.27469998598098755},{"id":"https://openalex.org/C98025372","wikidata":"https://www.wikidata.org/wiki/Q477538","display_name":"Systems architecture","level":3,"score":0.27079999446868896},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.26190000772476196},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.2587999999523163},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.2533999979496002},{"id":"https://openalex.org/C2779606945","wikidata":"https://www.wikidata.org/wiki/Q5145847","display_name":"Collaborative network","level":2,"score":0.2524000108242035}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.23975","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.23975","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.2603.23975","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.23975","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"collaborative":[1],"perception,":[2],"an":[3],"agent's":[4],"performance":[5,99,108],"can":[6],"be":[7],"degraded":[8],"by":[9],"heterogeneity":[10],"arising":[11],"from":[12,81],"differences":[13],"in":[14,75],"model":[15],"architecture":[16],"or":[17],"training":[18],"data":[19],"distributions.":[20],"To":[21],"address":[22],"this":[23,107],"challenge,":[24],"we":[25,64],"propose":[26,65],"HyDRA":[27,97],"(Hybrid":[28],"Domain-Aware":[29],"Robust":[30],"Architecture),":[31],"a":[32,42,47],"unified":[33],"pipeline":[34],"that":[35,51],"integrates":[36],"intermediate":[37,82],"and":[38,56],"late":[39,76],"fusion":[40,83],"within":[41],"domain-aware":[43],"framework.":[44],"We":[45],"introduce":[46],"lightweight":[48],"domain":[49],"classifier":[50],"dynamically":[52],"identifies":[53],"heterogeneous":[54],"agents":[55,116],"assigns":[57],"them":[58],"to":[59,70,101],"the":[60,112],"late-fusion":[61],"branch.":[62],"Furthermore,":[63],"anchor-guided":[66],"pose":[67],"graph":[68],"optimization":[69],"mitigate":[71],"localization":[72],"errors":[73],"inherent":[74],"fusion,":[77],"leveraging":[78],"reliable":[79],"detections":[80],"as":[84,111],"fixed":[85],"spatial":[86],"anchors.":[87],"Extensive":[88],"experiments":[89],"demonstrate":[90],"that,":[91],"despite":[92],"requiring":[93],"no":[94],"additional":[95],"training,":[96],"achieves":[98],"comparable":[100],"state-of-the-art":[102],"heterogeneity-aware":[103],"CP":[104],"methods.":[105],"Importantly,":[106],"is":[109],"maintained":[110],"number":[113],"of":[114],"collaborating":[115],"increases,":[117],"enabling":[118],"zero-cost":[119],"scaling":[120],"without":[121],"retraining.":[122]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-27T00:00:00"}