{"id":"https://openalex.org/W7161543352","doi":"https://doi.org/10.48550/arxiv.2605.15733","title":"Structure Abstraction and Generalization in a Hippocampal-Entorhinal Inspired World Model","display_name":"Structure Abstraction and Generalization in a Hippocampal-Entorhinal Inspired World Model","publication_year":2026,"publication_date":"2026-05-15","ids":{"openalex":"https://openalex.org/W7161543352","doi":"https://doi.org/10.48550/arxiv.2605.15733"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.15733","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.15733","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.2605.15733","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136441399","display_name":"Tianqiu Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Tianqiu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057657290","display_name":"Muyang Lyu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lyu, Muyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136374270","display_name":"Xiao Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Xiao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136416657","display_name":"Si Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Si","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/T10448","display_name":"Memory and Neural Mechanisms","score":0.9144999980926514,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10448","display_name":"Memory and Neural Mechanisms","score":0.9144999980926514,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11431","display_name":"Action Observation and Synchronization","score":0.02160000056028366,"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/T11094","display_name":"Face Recognition and Perception","score":0.006899999920278788,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/abstraction","display_name":"Abstraction","score":0.6510000228881836},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5562999844551086},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5358999967575073},{"id":"https://openalex.org/keywords/reuse","display_name":"Reuse","score":0.48089998960494995},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.44609999656677246},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.39640000462532043},{"id":"https://openalex.org/keywords/abstraction-layer","display_name":"Abstraction layer","score":0.3880999982357025},{"id":"https://openalex.org/keywords/spatial-intelligence","display_name":"Spatial intelligence","score":0.36059999465942383}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7386000156402588},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.6510000228881836},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6046000123023987},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5562999844551086},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5358999967575073},{"id":"https://openalex.org/C206588197","wikidata":"https://www.wikidata.org/wiki/Q846574","display_name":"Reuse","level":2,"score":0.48089998960494995},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4627000093460083},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.44609999656677246},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.39640000462532043},{"id":"https://openalex.org/C147358964","wikidata":"https://www.wikidata.org/wiki/Q1200992","display_name":"Abstraction layer","level":3,"score":0.3880999982357025},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3691999912261963},{"id":"https://openalex.org/C155911833","wikidata":"https://www.wikidata.org/wiki/Q3817354","display_name":"Spatial intelligence","level":2,"score":0.36059999465942383},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.3564999997615814},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2939000129699707},{"id":"https://openalex.org/C2777508537","wikidata":"https://www.wikidata.org/wiki/Q7936620","display_name":"Visual reasoning","level":2,"score":0.28839999437332153},{"id":"https://openalex.org/C13606891","wikidata":"https://www.wikidata.org/wiki/Q2623243","display_name":"Conceptual model","level":2,"score":0.2777999937534332},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.27480000257492065},{"id":"https://openalex.org/C131584629","wikidata":"https://www.wikidata.org/wiki/Q4308705","display_name":"Coupling (piping)","level":2,"score":0.26669999957084656},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.263700008392334},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.2599000036716461},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.25130000710487366},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2500999867916107}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.15733","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.15733","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.2605.15733","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.15733","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":{"Humans":[0],"abstract":[1,32,139],"experiences":[2],"into":[3],"structured":[4],"representations":[5],"to":[6,20],"facilitate":[7],"pattern":[8],"inference":[9],"and":[10,24,52,108],"knowledge":[11],"transfer.":[12],"While":[13],"the":[14,27,92,103,135],"hippocampal-entorhinal":[15],"(HPC-MEC)":[16],"circuit":[17],"is":[18],"known":[19],"represent":[21],"both":[22],"spatial":[23],"conceptual":[25],"spaces,":[26],"mechanisms":[28],"for":[29,65,95,125],"concurrently":[30],"extracting":[31],"structures":[33,76],"from":[34,78],"continuous,":[35],"high-dimensional":[36],"dynamics":[37,86],"remain":[38],"poorly":[39],"understood.":[40],"We":[41],"propose":[42],"a":[43,54,88,121],"brain-inspired":[44],"hierarchical":[45],"model":[46,64,72],"that":[47,73],"simultaneously":[48],"infers":[49],"latent":[50],"transitions":[51],"constructs":[53],"predictive":[55],"visual":[56],"world":[57,132],"model.":[58],"Our":[59],"architecture":[60],"employs":[61],"an":[62,69],"inverse":[63],"structural":[66,96,109,116],"extraction":[67],"alongside":[68],"HPC-MEC":[70],"coupling":[71],"dissociates":[74],"relational":[75],"(MEC)":[77],"integrated":[79],"episodic":[80],"scenes":[81],"(HPC).":[82],"Using":[83],"primitive":[84],"transformation":[85],"as":[87],"benchmark,":[89],"we":[90],"demonstrate":[91],"model's":[93],"capacity":[94],"abstraction.":[97],"By":[98],"leveraging":[99],"velocity-driven":[100],"path":[101],"integration,":[102],"framework":[104,124],"enables":[105],"robust":[106],"prediction":[107],"reuse":[110],"across":[111],"diverse":[112],"contexts,":[113],"thereby":[114],"achieving":[115],"generalization.":[117],"This":[118],"work":[119],"provides":[120],"novel":[122],"computational":[123],"understanding":[126],"how":[127],"brain-inspired,":[128],"self-supervised":[129],"learning":[130],"of":[131,137],"models":[133],"facilitates":[134],"acquisition":[136],"reusable":[138],"knowledge.":[140]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-19T00:00:00"}
