{"id":"https://openalex.org/W7155654787","doi":null,"title":"ReCAPA: Hierarchical Predictive Correction to Mitigate Cascading Failures","display_name":"ReCAPA: Hierarchical Predictive Correction to Mitigate Cascading Failures","publication_year":2026,"publication_date":"2026-04-23","ids":{"openalex":"https://openalex.org/W7155654787"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2604.21232","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2604.21232","pdf_url":"https://arxiv.org/pdf/2604.21232","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"erratum","is_traditional":true,"indexed_in":["arxiv"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2604.21232","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102685914","display_name":"Xiyin Zeng","orcid":"https://orcid.org/0009-0000-4849-3949","observed_orcids":["https://orcid.org/0009-0000-4849-3949"]},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]},{"id":"https://openalex.org/I4405261251","display_name":"The Hong Kong University of Science and Technology (Guangzhou)","ror":"https://ror.org/050h0vm43","country_code":"CN","type":"education","lineage":["https://openalex.org/I4405261251"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zeng, Xiyin","raw_affiliation_strings":["Hong Kong University of Science and Technology ( Guangzhou )","South China Normal University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hong Kong University of Science and Technology ( Guangzhou )","institution_ids":["https://openalex.org/I4405261251"]},{"raw_affiliation_string":"South China Normal University","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134476587","display_name":"Yuyu Sun","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sun, Yuyu","raw_affiliation_strings":["South China Normal University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South China Normal University","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134595656","display_name":"Haoyang Li","orcid":"https://orcid.org/0009-0004-7346-5535","observed_orcids":["https://orcid.org/0009-0004-7346-5535"]},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li, Haoyang","raw_affiliation_strings":["South China Normal University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South China Normal University","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134528415","display_name":"Shouqiang Liu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liu, Shouqiang","raw_affiliation_strings":["South China Normal University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South China Normal University","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100446112","display_name":"Hao Wang","orcid":"https://orcid.org/0000-0002-3086-3128","observed_orcids":["https://orcid.org/0000-0002-3086-3128","https://orcid.org/0000-0003-1662-2480"]},"institutions":[{"id":"https://openalex.org/I4405261251","display_name":"The Hong Kong University of Science and Technology (Guangzhou)","ror":"https://ror.org/050h0vm43","country_code":"CN","type":"education","lineage":["https://openalex.org/I4405261251"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wang, Hao","raw_affiliation_strings":["Hong Kong University of Science and Technology ( Guangzhou )"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hong Kong University of Science and Technology ( Guangzhou )","institution_ids":["https://openalex.org/I4405261251"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.4918999969959259,"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"}},"topics":[{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.4918999969959259,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.2957000136375427,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10906","display_name":"AI-based Problem Solving and Planning","score":0.09610000252723694,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cascading-failures","display_name":"cascading failures","score":0.9340000152587891},{"id":"https://openalex.org/keywords/error-propagation","display_name":"error propagation","score":0.9539999961853027},{"id":"https://openalex.org/keywords/semantic-alignment","display_name":"semantic alignment","score":0.7770000100135803},{"id":"https://openalex.org/keywords/hierarchical-planning","display_name":"hierarchical planning","score":0.5789999961853027},{"id":"https://openalex.org/keywords/trajectory-alignment","display_name":"trajectory alignment","score":0.5379999876022339},{"id":"https://openalex.org/keywords/sinkhorn-algorithm","display_name":"Sinkhorn algorithm","score":0.5289999842643738},{"id":"https://openalex.org/keywords/embodied-agents","display_name":"embodied agents","score":0.753000020980835},{"id":"https://openalex.org/keywords/ai2-thor","display_name":"AI2-THOR","score":0.9950000047683716}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8019000291824341},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6470999717712402},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.5645999908447266},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.41370001435279846},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39750000834465027},{"id":"https://openalex.org/C103088060","wikidata":"https://www.wikidata.org/wiki/Q1062839","display_name":"Error detection and correction","level":2,"score":0.35989999771118164},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.35920000076293945},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34929999709129333},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.33889999985694885},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3361000120639801},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.3336000144481659},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.32659998536109924},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.32010000944137573},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.29829999804496765},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.29739999771118164},{"id":"https://openalex.org/C167085575","wikidata":"https://www.wikidata.org/wiki/Q6803654","display_name":"Mean squared prediction error","level":2,"score":0.2883000075817108},{"id":"https://openalex.org/C2776544517","wikidata":"https://www.wikidata.org/wiki/Q189447","display_name":"Unexpected events","level":2,"score":0.27489998936653137},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.27219998836517334},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.2712000012397766},{"id":"https://openalex.org/C70452415","wikidata":"https://www.wikidata.org/wiki/Q3182448","display_name":"Predictive maintenance","level":2,"score":0.2603999972343445},{"id":"https://openalex.org/C123614077","wikidata":"https://www.wikidata.org/wiki/Q1364905","display_name":"Propagation of uncertainty","level":2,"score":0.2542000114917755}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:arXiv.org:2604.21232","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2604.21232","pdf_url":"https://arxiv.org/pdf/2604.21232","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2604.21232","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2604.21232","pdf_url":"https://arxiv.org/pdf/2604.21232","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G8721675579","display_name":null,"funder_award_id":"62406267","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335480","display_name":"Guangzhou Municipal Science and Technology Project","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7155654787.pdf","grobid_xml":"https://content.openalex.org/works/W7155654787.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W2736601468","https://openalex.org/W2776202271","https://openalex.org/W3110257065","https://openalex.org/W3126325318","https://openalex.org/W3207057769","https://openalex.org/W4327810158","https://openalex.org/W4361806741","https://openalex.org/W4366850747","https://openalex.org/W4383473935","https://openalex.org/W4386185600","https://openalex.org/W4387561528","https://openalex.org/W4392679398","https://openalex.org/W4392872989","https://openalex.org/W4399837985","https://openalex.org/W4400601342","https://openalex.org/W4402711432","https://openalex.org/W4403364427","https://openalex.org/W4403798678","https://openalex.org/W4404330874","https://openalex.org/W4404782171","https://openalex.org/W4404782952","https://openalex.org/W4404792748","https://openalex.org/W4405172832","https://openalex.org/W4405766390","https://openalex.org/W4415796627","https://openalex.org/W6910543424","https://openalex.org/W6948369276","https://openalex.org/W7133215713","https://openalex.org/W7133222210","https://openalex.org/W7133224126"],"related_works":["https://openalex.org/W7204865727","https://openalex.org/W7214406001","https://openalex.org/W7214044120","https://openalex.org/W7134916114","https://openalex.org/W4414428140","https://openalex.org/W7128859932","https://openalex.org/W7208819338","https://openalex.org/W4415951582","https://openalex.org/W4414818035","https://openalex.org/W7137849948"],"abstract_inverted_index":{"Vision-Language-Action":[0],"systems":[1],"follow":[2],"instructions":[3],"to":[4,67,106,110,123],"execute":[5],"multi-step":[6],"tasks":[7],"in":[8,130],"multimodal":[9],"environments.":[10],"Recent":[11],"VLA":[12],"approaches":[13],"typically":[14],"rely":[15],"on":[16,148],"post-hoc":[17],"correction":[18,94],"mechanisms":[19],"or":[20],"operate":[21],"under":[22],"fixed":[23],"task":[24],"decompositions":[25],"and":[26,42,57,65,75,88,95,127,136,156,161],"alignment":[27,78,96],"schemes.":[28],"However,":[29],"once":[30],"an":[31],"intermediate":[32],"step":[33],"is":[34,79],"mis-specified,":[35],"local":[36],"errors":[37],"propagate":[38],"through":[39],"subsequent":[40],"steps":[41,109],"eventually":[43],"accumulate":[44],"into":[45],"cascading":[46],"failures.":[47],"To":[48],"mitigate":[49],"this":[50],"compounding":[51],"effect,":[52],"we":[53],"propose":[54],"Predictive":[55],"Alignment":[56],"Planning":[58],"Architecture,":[59],"a":[60,85,89],"framework":[61],"that":[62,143],"uses":[63],"prediction":[64],"contrast":[66],"adjust":[68,107],"deviations":[69],"across":[70],"three":[71],"levels:":[72],"actions,":[73],"subgoals,":[74],"trajectories.":[76],"Semantic":[77],"enforced":[80],"at":[81],"all":[82],"levels":[83],"using":[84],"Sinkhorn-based":[86],"module":[87],"Score-field":[90],"module.":[91],"The":[92],"predictive":[93],"jointly":[97],"update":[98],"the":[99,114],"action":[100],"generator":[101],"during":[102],"training,":[103],"enabling":[104],"it":[105],"fine-grained":[108],"remain":[111],"aligned":[112],"with":[113],"overall":[115],"intent.":[116],"We":[117],"further":[118],"introduce":[119],"two":[120],"new":[121],"metrics":[122],"quantify":[124],"error":[125],"propagation":[126],"recovery":[128],"processes":[129],"tasks,":[131],"capturing":[132],"how":[133],"mistakes":[134],"spread":[135],"fade":[137],"over":[138],"long-horizon":[139],"execution.":[140],"Experiments":[141],"show":[142],"ReCAPA":[144],"achieves":[145],"competitive":[146],"results":[147],"embodied":[149],"agent":[150],"benchmarks":[151],"such":[152],"as":[153],"VisualAgentBench,":[154],"MineDojo,":[155],"AI2-THOR,":[157],"outperforming":[158],"strong":[159],"proprietary":[160],"open-source":[162],"Large":[163],"Language":[164],"Model":[165],"baselines.":[166]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-04-26T00:00:00"}