{"id":"https://openalex.org/W7143540832","doi":"https://doi.org/10.48550/arxiv.2603.25903","title":"Emergent Neural Automaton Policies: Learning Symbolic Structure from Visuomotor Trajectories","display_name":"Emergent Neural Automaton Policies: Learning Symbolic Structure from Visuomotor Trajectories","publication_year":2026,"publication_date":"2026-03-26","ids":{"openalex":"https://openalex.org/W7143540832","doi":"https://doi.org/10.48550/arxiv.2603.25903"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.25903","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.25903","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.25903","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100717341","display_name":"Yiyuan Pan","orcid":"https://orcid.org/0000-0002-2875-0503"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Pan, Yiyuan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009405571","display_name":"Xusheng Luo","orcid":"https://orcid.org/0000-0003-4342-7234"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Xusheng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039258932","display_name":"Hanjiang Hu","orcid":"https://orcid.org/0000-0002-5698-5887"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Hanjiang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130937070","display_name":"Peiqi Yu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Peiqi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5130983828","display_name":"Changliu Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Changliu","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100717341"],"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":0.5299999713897705,"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":0.5299999713897705,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.14030000567436218,"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/T11685","display_name":"Zebrafish Biomedical Research Applications","score":0.08810000121593475,"subfield":{"id":"https://openalex.org/subfields/1307","display_name":"Cell Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.77920001745224},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5925999879837036},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5246000289916992},{"id":"https://openalex.org/keywords/automaton","display_name":"Automaton","score":0.4993000030517578},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.42160001397132874},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.3984000086784363},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.39419999718666077},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.3734999895095825},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.3714999854564667},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.3610000014305115}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.77920001745224},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7484999895095825},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6881999969482422},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5925999879837036},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5246000289916992},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5126000046730042},{"id":"https://openalex.org/C112505250","wikidata":"https://www.wikidata.org/wiki/Q787116","display_name":"Automaton","level":2,"score":0.4993000030517578},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.42160001397132874},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.3984000086784363},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.39419999718666077},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3734999895095825},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.3714999854564667},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.3610000014305115},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.3582000136375427},{"id":"https://openalex.org/C167822520","wikidata":"https://www.wikidata.org/wiki/Q176452","display_name":"Finite-state machine","level":2,"score":0.3549000024795532},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.33399999141693115},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.3327000141143799},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.33009999990463257},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.3188000023365021},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.31200000643730164},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.31049999594688416},{"id":"https://openalex.org/C2776999362","wikidata":"https://www.wikidata.org/wiki/Q2349274","display_name":"Planner","level":2,"score":0.30640000104904175},{"id":"https://openalex.org/C2778029271","wikidata":"https://www.wikidata.org/wiki/Q5421931","display_name":"Extension (predicate logic)","level":2,"score":0.3010999858379364},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.28299999237060547},{"id":"https://openalex.org/C8521452","wikidata":"https://www.wikidata.org/wiki/Q203790","display_name":"Connectionism","level":3,"score":0.2824000120162964},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2773999869823456},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2770000100135803},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.27480000257492065},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.2630999982357025},{"id":"https://openalex.org/C2779038628","wikidata":"https://www.wikidata.org/wiki/Q7248497","display_name":"Programming by demonstration","level":3,"score":0.26100000739097595},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.25459998846054077},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.25360000133514404}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.25903","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.25903","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.25903","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.25903","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":"article"},"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":{"Scaling":[0],"robot":[1],"learning":[2],"to":[3,69,99,150],"long-horizon":[4,137],"tasks":[5,138],"remains":[6],"a":[7,43,47,71,94,157],"formidable":[8],"challenge.":[9],"While":[10],"end-to-end":[11,145],"policies":[12,147],"often":[13],"lack":[14],"the":[15,34,66,111],"structural":[16],"priors":[17],"needed":[18],"for":[19],"effective":[20],"long-term":[21],"reasoning,":[22],"traditional":[23],"neuro-symbolic":[24,49],"methods":[25],"rely":[26],"heavily":[27],"on":[28,133],"hand-crafted":[29],"symbolic":[30],"priors.":[31],"To":[32],"address":[33],"issue,":[35],"we":[36,57],"introduce":[37],"ENAP":[38,120,141],"(Emergent":[39],"Neural":[40],"Automaton":[41],"Policy),":[42],"framework":[44],"that":[45,140],"allows":[46],"bi-level":[48],"policy":[50],"adaptively":[51],"emerge":[52],"from":[53,75],"visuomotor":[54,76],"demonstrations.":[55],"Specifically,":[56],"first":[58],"employ":[59],"adaptive":[60],"clustering":[61],"and":[62,117,125,136],"an":[63,81],"extension":[64],"of":[65,160],"L*":[67],"algorithm":[68],"infer":[70],"Mealy":[72],"state":[73],"machine":[74],"data,":[77],"which":[78],"serves":[79],"as":[80],"interpretable":[82],"high-level":[83],"planner":[84],"capturing":[85],"latent":[86],"task":[87,112],"modes.":[88],"Then,":[89],"this":[90],"discrete":[91,115],"structure":[92,113],"guides":[93],"low-level":[95],"reactive":[96],"residual":[97],"network":[98],"learn":[100],"precise":[101],"continuous":[102,118],"control":[103],"via":[104],"behavior":[105],"cloning":[106],"(BC).":[107],"By":[108],"explicitly":[109],"modeling":[110],"with":[114],"transitions":[116],"residuals,":[119],"achieves":[121],"high":[122],"sample":[123],"efficiency":[124],"interpretability":[126],"without":[127],"requiring":[128],"task-specific":[129],"labels.":[130],"Extensive":[131],"experiments":[132],"complex":[134],"manipulation":[135],"demonstrate":[139],"outperforms":[142],"state-of-the-art":[143],"(SoTA)":[144],"VLA":[146],"by":[148],"up":[149],"27%":[151],"in":[152],"low-data":[153],"regimes,":[154],"while":[155],"offering":[156],"structured":[158],"representation":[159],"robotic":[161],"intent":[162],"(Fig.":[163],"1).":[164]},"counts_by_year":[],"updated_date":"2026-03-31T06:07:48.031334","created_date":"2026-03-31T00:00:00"}