{"id":"https://openalex.org/W7164401449","doi":"https://doi.org/10.48550/arxiv.2606.12334","title":"Fourier Features Let Agents Learn High Precision Policies with Imitation Learning","display_name":"Fourier Features Let Agents Learn High Precision Policies with Imitation Learning","publication_year":2026,"publication_date":"2026-06-10","ids":{"openalex":"https://openalex.org/W7164401449","doi":"https://doi.org/10.48550/arxiv.2606.12334"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.12334","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.12334","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":"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.2606.12334","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037406540","display_name":"Bal\u00e1zs Gyenes","orcid":"https://orcid.org/0000-0002-4430-1820"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gyenes, Bal\u00e1zs","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114637377","display_name":"Emiliyan Gospodinov","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gospodinov, Emiliyan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045994562","display_name":"Jan von Frieling","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Frieling, Jan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116849341","display_name":"Enrico Krohmer","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Krohmer, Enrico","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043085514","display_name":"Nicolas Schreiber","orcid":"https://orcid.org/0009-0008-1939-6566"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Schreiber, Nicolas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138449037","display_name":"Xiaogang Jia","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jia, Xiaogang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009347823","display_name":"Niklas Freymuth","orcid":"https://orcid.org/0009-0001-7755-6811"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Freymuth, Niklas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138427106","display_name":"Gerhard Neumann","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Neumann, Gerhard","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/T10653","display_name":"Robot Manipulation and Learning","score":0.8702999949455261,"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"}},"topics":[{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.8702999949455261,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.07490000128746033,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.008700000122189522,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6784999966621399},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.5526000261306763},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.526199996471405},{"id":"https://openalex.org/keywords/ambiguity","display_name":"Ambiguity","score":0.5213000178337097},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.5058000087738037},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.4869000017642975},{"id":"https://openalex.org/keywords/cartesian-coordinate-system","display_name":"Cartesian coordinate system","score":0.43059998750686646},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.4207000136375427}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6866999864578247},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6784999966621399},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.5526000261306763},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.526199996471405},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.5213000178337097},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.51419997215271},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.5058000087738037},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.4869000017642975},{"id":"https://openalex.org/C16038011","wikidata":"https://www.wikidata.org/wiki/Q62912","display_name":"Cartesian coordinate system","level":2,"score":0.43059998750686646},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.4207000136375427},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.41179999709129333},{"id":"https://openalex.org/C2779231336","wikidata":"https://www.wikidata.org/wiki/Q7534724","display_name":"Sketch","level":2,"score":0.41040000319480896},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3783000111579895},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36419999599456787},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.3635999858379364},{"id":"https://openalex.org/C189645446","wikidata":"https://www.wikidata.org/wiki/Q350865","display_name":"Mirroring","level":2,"score":0.36090001463890076},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2915000021457672},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.2736999988555908},{"id":"https://openalex.org/C207864730","wikidata":"https://www.wikidata.org/wiki/Q179467","display_name":"Fourier series","level":2,"score":0.2556999921798706}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.12334","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.12334","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":"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.2606.12334","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.12334","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":"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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"High-precision":[0],"robotic":[1],"manipulation":[2,117],"requires":[3],"fine-grained":[4],"spatial":[5],"reasoning":[6],"that":[7,25,54,136,156],"is":[8],"often":[9],"difficult":[10],"to":[11,17,60,84,104],"achieve":[12],"with":[13,101],"RGB-only":[14],"policies":[15,160],"due":[16,59],"depth":[18],"ambiguity":[19],"and":[20,122,125,146,148,185],"perspective":[21],"scale":[22],"issues.":[23],"Policies":[24],"leverage":[26,161],"3D":[27],"information":[28],"directly,":[29],"such":[30],"as":[31,172],"those":[32],"based":[33],"on":[34,77,115,126,187],"point":[35,86,98,177],"clouds,":[36],"offer":[37],"a":[38,127,173],"stronger":[39],"geometric":[40,162],"prior":[41],"over":[42],"purely":[43],"image-based":[44],"ones,":[45],"yet":[46],"their":[47,132,170],"performance":[48],"remains":[49],"highly":[50],"task-dependent.":[51],"We":[52,81,107,181],"hypothesize":[53],"this":[55],"discrepancy":[56],"may":[57],"be":[58],"the":[61,97,110,120],"spectral":[62],"bias":[63],"of":[64,112],"neural":[65],"networks":[66],"towards":[67],"learning":[68],"low":[69],"frequency":[70],"functions,":[71],"which":[72],"especially":[73],"affects":[74],"architectures":[75,145],"conditioned":[76],"slow-moving":[78],"Cartesian":[79,89,167],"features.":[80,106],"thus":[82],"propose":[83],"map":[85],"clouds":[87],"from":[88,119],"space":[90],"into":[91],"high-dimensional":[92],"Fourier":[93,113,137,157],"space,":[94],"effectively":[95,165],"equipping":[96],"cloud":[99],"encoder":[100,144],"direct":[102],"access":[103],"high-frequency":[105],"experimentally":[108],"validate":[109],"use":[111],"features":[114,138,158],"challenging":[116],"tasks":[118],"RoboCasa":[121],"ManiSkill3":[123],"benchmarks":[124,147],"real":[128],"robot":[129],"setup.":[130],"Despite":[131],"simplicity,":[133],"we":[134],"find":[135],"provide":[139,182],"significant":[140],"benefits":[141],"across":[142,151],"diverse":[143],"are":[149],"robust":[150],"hyperparameters.":[152],"Our":[153],"results":[154],"indicate":[155],"let":[159],"details":[163],"more":[164],"than":[166],"features,":[168],"showing":[169],"potential":[171],"general-purpose":[174],"tool":[175],"for":[176],"cloud-based":[178],"imitation":[179],"learning.":[180],"source":[183],"code":[184],"videos":[186],"our":[188],"project":[189],"page:":[190],"https://fourier-il.github.io/fourier-il":[191]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-12T00:00:00"}
