{"id":"https://openalex.org/W4401246959","doi":"https://doi.org/10.1109/lra.2024.3438036","title":"LVDiffusor: Distilling Functional Rearrangement Priors From Large Models Into Diffusor","display_name":"LVDiffusor: Distilling Functional Rearrangement Priors From Large Models Into Diffusor","publication_year":2024,"publication_date":"2024-08-02","ids":{"openalex":"https://openalex.org/W4401246959","doi":"https://doi.org/10.1109/lra.2024.3438036"},"language":"en","primary_location":{"id":"doi:10.1109/lra.2024.3438036","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2024.3438036","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5009381033","display_name":"Yiming Zeng","orcid":"https://orcid.org/0000-0003-2935-4067"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiming Zeng","raw_affiliation_strings":["School of Computer Science and Engineering, Sun Yat-Sen University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-2935-4067","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Sun Yat-Sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102718289","display_name":"Mingdong Wu","orcid":"https://orcid.org/0009-0007-9120-4621"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingdong Wu","raw_affiliation_strings":["Hyperplane Lab, School of CS, Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0007-9120-4621","affiliations":[{"raw_affiliation_string":"Hyperplane Lab, School of CS, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011037821","display_name":"Yang Long","orcid":"https://orcid.org/0000-0002-2445-6112"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Long Yang","raw_affiliation_strings":["Hyperplane Lab, School of CS, Peking University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hyperplane Lab, School of CS, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103231833","display_name":"Jiyao Zhang","orcid":"https://orcid.org/0009-0009-6150-2788"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiyao Zhang","raw_affiliation_strings":["Hyperplane Lab, School of CS, Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0009-6150-2788","affiliations":[{"raw_affiliation_string":"Hyperplane Lab, School of CS, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060192540","display_name":"Hao Ding","orcid":"https://orcid.org/0000-0002-1416-7050"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Ding","raw_affiliation_strings":["School of Computer Science and Engineering, Sun Yat-Sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Sun Yat-Sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101409148","display_name":"Hui Cheng","orcid":"https://orcid.org/0000-0003-2579-7004"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui Cheng","raw_affiliation_strings":["School of Computer Science and Engineering, Sun Yat-Sen University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-2579-7004","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Sun Yat-Sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100709867","display_name":"Hao Dong","orcid":"https://orcid.org/0000-0002-7984-9909"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Dong","raw_affiliation_strings":["Hyperplane Lab, School of CS, Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-7984-9909","affiliations":[{"raw_affiliation_string":"Hyperplane Lab, School of CS, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.4288,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.8128372,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"9","issue":"10","first_page":"8258","last_page":"8265"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10015","display_name":"Genomics and Phylogenetic Studies","score":0.41350001096725464,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular 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"}},"topics":[{"id":"https://openalex.org/T10015","display_name":"Genomics and Phylogenetic Studies","score":0.41350001096725464,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular 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"}},{"id":"https://openalex.org/T11269","display_name":"Algorithms and Data Compression","score":0.3993000090122223,"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/T10885","display_name":"Gene expression and cancer classification","score":0.392300009727478,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular 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/prior-probability","display_name":"Prior probability","score":0.6990877389907837},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.48442724347114563},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.420624703168869},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.20265606045722961},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.0952642560005188}],"concepts":[{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.6990877389907837},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.48442724347114563},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.420624703168869},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.20265606045722961},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.0952642560005188}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lra.2024.3438036","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2024.3438036","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.46000000834465027}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W2013035813","https://openalex.org/W2016435525","https://openalex.org/W2119618626","https://openalex.org/W2144144709","https://openalex.org/W2415355599","https://openalex.org/W2463220900","https://openalex.org/W2798622261","https://openalex.org/W2897326507","https://openalex.org/W2973511309","https://openalex.org/W3202948970","https://openalex.org/W3206916018","https://openalex.org/W4224912544","https://openalex.org/W4225125774","https://openalex.org/W4312594400","https://openalex.org/W4312807436","https://openalex.org/W4312933868","https://openalex.org/W4367721889","https://openalex.org/W4383097638","https://openalex.org/W4383108296","https://openalex.org/W4385403813","https://openalex.org/W4385430679","https://openalex.org/W4385473486","https://openalex.org/W4386075912","https://openalex.org/W4388660746","https://openalex.org/W4388720459","https://openalex.org/W4393154152","https://openalex.org/W6748208425","https://openalex.org/W6784840303","https://openalex.org/W6786375611","https://openalex.org/W6791353385","https://openalex.org/W6803928713","https://openalex.org/W6809646742","https://openalex.org/W6809885388","https://openalex.org/W6811467201","https://openalex.org/W6842248158","https://openalex.org/W6849177959","https://openalex.org/W6850071225","https://openalex.org/W6850787431","https://openalex.org/W6850975553","https://openalex.org/W6853146131","https://openalex.org/W6853982971","https://openalex.org/W6854929498","https://openalex.org/W6855028510","https://openalex.org/W6856574445"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W4391375266","https://openalex.org/W2580650124","https://openalex.org/W4386190339","https://openalex.org/W2968424575","https://openalex.org/W3142333283","https://openalex.org/W3122088529","https://openalex.org/W3041320102","https://openalex.org/W2111669074","https://openalex.org/W2085259108"],"abstract_inverted_index":{"Object":[0],"rearrangement,":[1],"a":[2,64,94],"fundamental":[3],"challenge":[4],"in":[5,132,144],"robotics,":[6],"demands":[7],"versatile":[8],"strategies":[9],"to":[10,25,30,71,116],"handle":[11],"diverse":[12,80],"objects,":[13],"configurations,":[14],"and":[15,57,86,88,110],"functional":[16,27,37,73,118],"needs.":[17],"To":[18],"achieve":[19],"this,":[20],"the":[21,36,91,100,107,112,139],"AI":[22],"robot":[23],"needs":[24],"learn":[26,42],"rearrangement":[28,74,150],"priors":[29,44],"specify":[31],"precise":[32],"goals":[33,147],"that":[34,67],"meet":[35,117],"requirements.":[38,119],"Previous":[39],"methods":[40],"typically":[41],"such":[43],"from":[45],"either":[46],"laborious":[47],"human":[48],"annotations":[49],"or":[50],"manually":[51],"designed":[52],"heuristics,":[53],"which":[54],"limits":[55],"scalability":[56],"generalization.":[58],"In":[59,120],"this":[60,121],"letter,":[61],"we":[62,123],"propose":[63],"novel":[65],"approach":[66,78,143],"leverages":[68],"large":[69],"models":[70],"distill":[72],"priors.":[75],"Specifically,":[76],"our":[77,142],"collects":[79],"arrangement":[81],"examples":[82,92],"using":[83],"both":[84],"LLMs":[85],"VLMs":[87],"then":[89],"distills":[90],"into":[93],"diffusion":[95,102],"model.":[96],"During":[97],"test":[98],"time,":[99],"learned":[101],"model":[103],"is":[104],"conditioned":[105],"on":[106],"initial":[108],"configuration":[109],"guides":[111],"positioning":[113],"of":[114,141],"objects":[115],"way,":[122],"balance":[124],"zero-shot":[125],"generalization":[126],"with":[127],"time":[128],"efficiency.":[129],"Extensive":[130],"experiments":[131],"multiple":[133],"domains,":[134],"including":[135],"real-world":[136],"scenarios,":[137],"demonstrate":[138],"effectiveness":[140],"generating":[145],"compatible":[146],"for":[148],"object":[149],"tasks,":[151],"significantly":[152],"outperforming":[153],"baseline":[154],"methods.":[155]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
