{"id":"https://openalex.org/W7168390481","doi":"https://doi.org/10.48550/arxiv.2607.12466","title":"Deployable Human Preference Alignment in Robotics: Learning Representative Rewards from Diverse Human Preferences","display_name":"Deployable Human Preference Alignment in Robotics: Learning Representative Rewards from Diverse Human Preferences","publication_year":2026,"publication_date":"2026-07-14","ids":{"openalex":"https://openalex.org/W7168390481","doi":"https://doi.org/10.48550/arxiv.2607.12466"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.12466","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.12466","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":null,"license_id":null,"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.2607.12466","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5140899065","display_name":"Taehyung Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Taehyung","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140877145","display_name":"Gwangmo Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee, Gwangmo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140955809","display_name":"Minjun Chang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chang, Minjun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140855864","display_name":"Sunghyun Lim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lim, Sunghyun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5140933105","display_name":"Jongeun Choi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Choi, Jongeun","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/T10709","display_name":"Social Robot Interaction and HRI","score":0.5406000018119812,"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"}},"topics":[{"id":"https://openalex.org/T10709","display_name":"Social Robot Interaction and HRI","score":0.5406000018119812,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.10869999974966049,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.05640000104904175,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/preference","display_name":"Preference","score":0.6905999779701233},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5856000185012817},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5789999961853027},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5641000270843506},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.47870001196861267},{"id":"https://openalex.org/keywords/preference-learning","display_name":"Preference learning","score":0.4779999852180481},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.46380001306533813},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.36250001192092896}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7099999785423279},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.6905999779701233},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5903000235557556},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5856000185012817},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5789999961853027},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5715000033378601},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5641000270843506},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.47870001196861267},{"id":"https://openalex.org/C181204326","wikidata":"https://www.wikidata.org/wiki/Q7239820","display_name":"Preference learning","level":3,"score":0.4779999852180481},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.46380001306533813},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.36250001192092896},{"id":"https://openalex.org/C32172795","wikidata":"https://www.wikidata.org/wiki/Q4692266","display_name":"Aggregation problem","level":2,"score":0.34779998660087585},{"id":"https://openalex.org/C90329073","wikidata":"https://www.wikidata.org/wiki/Q914232","display_name":"Ask price","level":2,"score":0.3418999910354614},{"id":"https://openalex.org/C153668964","wikidata":"https://www.wikidata.org/wiki/Q27636","display_name":"Majority rule","level":2,"score":0.3174000084400177},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.2992999851703644},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2919999957084656},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.287200003862381},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.28110000491142273},{"id":"https://openalex.org/C2781316041","wikidata":"https://www.wikidata.org/wiki/Q1230584","display_name":"Diversity (politics)","level":2,"score":0.2777000069618225},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.2766999900341034},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.27379998564720154},{"id":"https://openalex.org/C145460709","wikidata":"https://www.wikidata.org/wiki/Q859951","display_name":"Human\u2013robot interaction","level":3,"score":0.2648000121116638},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.2574000060558319},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.25279998779296875}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.12466","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.12466","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2607.12466","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.12466","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7831491827964783}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Aligning":[0],"robot":[1],"policies":[2,39,86,231],"with":[3,233],"human":[4,30],"preferences":[5,61],"is":[6,20,159],"essential":[7],"for":[8,161,168],"deployment":[9],"to":[10,29,50,58,116,141],"diverse":[11,93,204],"end":[12],"users.":[13,94],"In":[14],"per-user":[15,125,251],"alignment":[16,52,252],"approach,":[17],"preference":[18,31,89,103,153],"feedback":[19],"often":[21,63],"sparse,":[22],"so":[23],"learning":[24],"becomes":[25],"unstable":[26],"and":[27,33,62,101,111,127,144,178,228,248],"vulnerable":[28],"noise,":[32],"a":[34,77,82,96,118,146,157,190],"growing":[35],"number":[36,171,192],"of":[37,85,98,172,182,193],"individualized":[38],"makes":[40],"validation":[41,198],"difficult":[42],"before":[43],"deployment.":[44,201],"A":[45],"single":[46,244],"shared":[47,120],"policy":[48,158],"approach":[49,247],"user":[51,99,177],"avoids":[53],"this":[54,135],"cost":[55],"but":[56],"fails":[57],"capture":[59],"heterogeneous":[60],"neglects":[64],"minority":[65],"preferences.":[66],"To":[67],"address":[68],"these":[69],"challenges,":[70],"we":[71],"introduce":[72],"Preference-based":[73],"REward":[74],"Clustering":[75,164],"(PREC),":[76],"novel":[78],"framework":[79],"that":[80,209],"learns":[81,145],"compact":[83],"set":[84],"from":[87,155,175],"binary":[88],"labels":[90,109,173],"provided":[91],"by":[92],"From":[95],"dataset":[97],"trajectories":[100,113],"their":[102],"labels,":[104,154],"PREC":[105,137,210,234],"first":[106],"sets":[107],"the":[108,169,180,186,197],"aside":[110],"aggregates":[112],"across":[114,203],"users":[115,140,166,212],"learn":[117],"population-level":[119],"trajectory":[121,216],"encoder,":[122],"alleviating":[123],"limited":[124,170],"coverage":[126],"avoiding":[128],"label":[129,183,214],"noise":[130],"during":[131],"representation":[132],"learning.":[133],"Using":[134],"representation,":[136],"jointly":[138],"assigns":[139],"preference-coherent":[142,219],"clusters":[143,220],"representative":[147],"reward":[148,194],"model":[149],"per":[150],"cluster":[151],"using":[152],"which":[156],"optimized":[160],"each":[162,176],"cluster.":[163],"similar":[165],"compensates":[167],"available":[174],"mitigates":[179],"effect":[181],"noise.":[184],"At":[185],"same":[187],"time,":[188],"maintaining":[189],"manageable":[191],"models":[195],"reduces":[196],"burden":[199],"at":[200],"Experiments":[202],"simulated":[205],"locomotion":[206],"environments":[207],"show":[208],"groups":[211],"who":[213],"different":[215],"subsets":[217],"into":[218],"more":[221],"accurately":[222],"than":[223],"baseline":[224],"methods.":[225],"Under":[226],"sparse":[227],"noisy":[229],"feedback,":[230],"trained":[232],"improve":[235],"all":[236],"three":[237],"social":[238],"welfare":[239],"metrics":[240],"over":[241],"an":[242],"existing":[243],"shared-policy":[245],"user-alignment":[246],"even":[249],"outperform":[250],"approaches.":[253]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-16T00:00:00"}