{"id":"https://openalex.org/W7134823601","doi":"https://doi.org/10.48550/arxiv.2603.07875","title":"Choose What to Observe: Task-Aware Semantic-Geometric Representations for Visuomotor Policy","display_name":"Choose What to Observe: Task-Aware Semantic-Geometric Representations for Visuomotor Policy","publication_year":2026,"publication_date":"2026-03-09","ids":{"openalex":"https://openalex.org/W7134823601","doi":"https://doi.org/10.48550/arxiv.2603.07875"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.07875","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128677013","display_name":"Haoran Ding","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ding, Haoran","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128669421","display_name":"Liang Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Liang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100758451","display_name":"Yaxun Yang","orcid":"https://orcid.org/0000-0002-6539-9521"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Yaxun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128687823","display_name":"Wen Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Wen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128647332","display_name":"Tianyu Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Tianyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077958416","display_name":"Anqing Duan","orcid":"https://orcid.org/0000-0002-9666-018X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Duan, Anqing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128663331","display_name":"Xiaodan Liang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liang, Xiaodan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128677735","display_name":"Dezhen Song","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Dezhen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128656249","display_name":"Ivan Laptev","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Laptev, Ivan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128672776","display_name":"Yoshihiko Nakamura","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nakamura, Yoshihiko","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":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.25990598,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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":0.46140000224113464,"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":0.46140000224113464,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.12150000035762787,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.10029999911785126,"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/robustness","display_name":"Robustness (evolution)","score":0.6895999908447266},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.5364000201225281},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5023999810218811},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.4424000084400177},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4343000054359436},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.382099986076355},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.33149999380111694},{"id":"https://openalex.org/keywords/interface","display_name":"Interface (matter)","score":0.31929999589920044}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7164000272750854},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7074000239372253},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6895999908447266},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6190000176429749},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.5364000201225281},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5023999810218811},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.4424000084400177},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4343000054359436},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.382099986076355},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.33149999380111694},{"id":"https://openalex.org/C113843644","wikidata":"https://www.wikidata.org/wiki/Q901882","display_name":"Interface (matter)","level":4,"score":0.31929999589920044},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.30320000648498535},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.29760000109672546},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.2937000095844269},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2912999987602234},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2858999967575073},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.27559998631477356},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.2745000123977661},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.2565999925136566},{"id":"https://openalex.org/C111370547","wikidata":"https://www.wikidata.org/wiki/Q7451120","display_name":"Sensory cue","level":2,"score":0.2500999867916107}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.07875","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2603.07875","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.07875","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":"Preprint"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2603.07875","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[{"score":0.4001822769641876,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Visuomotor":[0],"policies":[1],"learned":[2],"from":[3,105],"demonstrations":[4],"often":[5],"overfit":[6],"to":[7,45,70],"nuisance":[8],"visual":[9,37,175],"factors":[10],"in":[11,16],"raw":[12],"RGB":[13,58],"observations,":[14],"resulting":[15],"brittle":[17],"behavior":[18],"under":[19,137,142,173],"appearance":[20,48,144],"shifts":[21],"such":[22],"as":[23],"background":[24],"changes":[25,49],"and":[26,60,75,146,152,156,162],"object":[27,74],"recoloring.":[28],"We":[29,77,129],"propose":[30],"a":[31,40,91,117,124],"task-aware":[32],"observation":[33,81,120],"interface":[34,165],"that":[35,122],"canonicalizes":[36],"input":[38],"into":[39,109],"shared":[41],"representation,":[42],"improving":[43,171],"robustness":[44,172],"out-of-distribution":[46],"(OOD)":[47],"without":[50],"modifying":[51],"or":[52],"fine-tuning":[53],"the":[54,72,110],"policy.":[55],"Given":[56],"an":[57,61,79],"image":[59],"open-vocabulary":[62],"specification":[63],"of":[64],"task-relevant":[65],"entities,":[66],"we":[67,100],"use":[68],"SAM3":[69],"segment":[71],"target":[73],"robot/gripper.":[76],"construct":[78],"L0":[80],"by":[82],"repainting":[83],"segmented":[84,111],"entities":[85],"with":[86],"predefined":[87],"semantic":[88],"colors":[89],"on":[90,131],"constant":[92],"background.":[93],"For":[94],"tasks":[95,141,150],"requiring":[96],"stronger":[97],"geometric":[98],"cues,":[99],"further":[101],"inject":[102],"monocular":[103],"depth":[104],"Depth":[106],"Anything":[107],"3":[108],"regions":[112],"via":[113],"depth-guided":[114],"overwrite,":[115],"yielding":[116],"unified":[118],"semantic--geometric":[119],"(L1)":[121],"remains":[123],"standard":[125],"3-channel,":[126],"image-like":[127],"input.":[128],"evaluate":[130],"RoboMimic":[132],"(Lift),":[133],"ManiSkill":[134],"YCB":[135],"grasping":[136],"clutter,":[138],"four":[139],"RLBench":[140],"controlled":[143],"shifts,":[145],"two":[147],"real-world":[148],"Franka":[149],"(ReachX":[151],"CloseCabinet).":[153],"Across":[154],"benchmarks":[155],"policy":[157],"backbones":[158],"(Flow":[159],"Matching":[160],"Policy":[161],"SmolVLA),":[163],"our":[164],"preserves":[166],"in-distribution":[167],"performance":[168],"while":[169],"substantially":[170],"OOD":[174],"shifts.":[176]},"counts_by_year":[],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2026-03-11T00:00:00"}