{"id":"https://openalex.org/W7164943463","doi":"https://doi.org/10.48550/arxiv.2606.15587","title":"Perfect Demo Makes Poor Teacher: Learning Robust Alignment from Critical Motion Segments","display_name":"Perfect Demo Makes Poor Teacher: Learning Robust Alignment from Critical Motion Segments","publication_year":2026,"publication_date":"2026-06-14","ids":{"openalex":"https://openalex.org/W7164943463","doi":"https://doi.org/10.48550/arxiv.2606.15587"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.15587","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.15587","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.15587","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035887801","display_name":"M Y Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Mingyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138720649","display_name":"Zeju Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Zeju","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138698677","display_name":"Jiuhe Shu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shu, Jiuhe","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138754742","display_name":"Hanqing Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Hanqing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111788017","display_name":"Yuhao Chao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chao, Yuhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138733645","display_name":"Hao Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Hao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138738995","display_name":"Chunhua Shen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shen, Chunhua","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":0.9753999710083008,"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":0.9753999710083008,"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":0.002899999963119626,"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/T12290","display_name":"Human Motion and Animation","score":0.0027000000700354576,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5960000157356262},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5685999989509583},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.5220000147819519},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.49149999022483826},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.45680001378059387},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.4381999969482422},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.4016999900341034},{"id":"https://openalex.org/keywords/counterintuitive","display_name":"Counterintuitive","score":0.35030001401901245},{"id":"https://openalex.org/keywords/motion-capture","display_name":"Motion capture","score":0.34860000014305115}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.692300021648407},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6043000221252441},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5960000157356262},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5685999989509583},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5485000014305115},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.5220000147819519},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.49149999022483826},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.45680001378059387},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.4381999969482422},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.4016999900341034},{"id":"https://openalex.org/C101097943","wikidata":"https://www.wikidata.org/wiki/Q5176983","display_name":"Counterintuitive","level":2,"score":0.35030001401901245},{"id":"https://openalex.org/C48007421","wikidata":"https://www.wikidata.org/wiki/Q676252","display_name":"Motion capture","level":3,"score":0.34860000014305115},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.34299999475479126},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.33719998598098755},{"id":"https://openalex.org/C2777723229","wikidata":"https://www.wikidata.org/wiki/Q4367921","display_name":"Learnability","level":2,"score":0.3303000032901764},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.321399986743927},{"id":"https://openalex.org/C150140777","wikidata":"https://www.wikidata.org/wiki/Q960648","display_name":"Point of interest","level":2,"score":0.30550000071525574},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.3001999855041504},{"id":"https://openalex.org/C3261483","wikidata":"https://www.wikidata.org/wiki/Q119565","display_name":"Frame rate","level":2,"score":0.28999999165534973},{"id":"https://openalex.org/C2780411076","wikidata":"https://www.wikidata.org/wiki/Q5462653","display_name":"Fluent","level":3,"score":0.28690001368522644},{"id":"https://openalex.org/C145565327","wikidata":"https://www.wikidata.org/wiki/Q852514","display_name":"Motion control","level":3,"score":0.2847000062465668},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.2800000011920929},{"id":"https://openalex.org/C150921843","wikidata":"https://www.wikidata.org/wiki/Q1170431","display_name":"Resampling","level":2,"score":0.27889999747276306},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2782999873161316},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.27570000290870667},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.27059999108314514},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.2623000144958496},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.2517000138759613}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.15587","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.15587","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.15587","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.15587","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":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.6300755739212036}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Expert":[0],"demonstrations":[1,31],"are":[2],"widely":[3],"assumed":[4],"to":[5,129,144,198],"be":[6,33],"the":[7,40,53,77,91,97,102,118,133,145,165,169,173,194,202],"gold":[8],"standard":[9],"for":[10,15,156,210,219],"robot":[11,216],"imitation":[12],"learning.":[13],"Yet":[14],"fine-grained":[16],"manipulation":[17],"such":[18],"as":[19],"insertion,":[20],"stacking,":[21],"and":[22,45,60,84,132,148,168],"alignment,":[23],"we":[24],"uncover":[25],"a":[26,48,123,159,211],"counterintuitive":[27],"failure":[28],"mode:":[29],"fluent":[30,187],"can":[32],"poor":[34],"teachers.":[35],"A":[36],"skilled":[37],"teleoperator":[38],"compresses":[39],"decisive":[41],"moments":[42],"of":[43,62,99,193,204,215],"alignment":[44,83],"recovery":[46,100],"into":[47,181],"brief":[49],"temporal":[50],"window,":[51],"leaving":[52],"policy":[54,103],"flooded":[55],"with":[56],"redundant":[57],"free-space":[58],"motion":[59,135,175],"starved":[61],"supervision":[63],"exactly":[64],"where":[65],"precision":[66],"determines":[67],"success.":[68],"We":[69,141],"address":[70],"this":[71],"bottleneck":[72],"at":[73],"two":[74],"levels.":[75],"At":[76],"data":[78,188],"level,":[79],"slowing":[80],"down":[81],"near":[82],"resampling":[85],"critical":[86],"segments":[87],"both":[88],"help,":[89],"yet":[90],"gain":[92,196],"comes":[93],"mainly":[94],"from":[95,107],"broadening":[96],"coverage":[98],"states":[101],"must":[104],"learn,":[105],"not":[106],"reweighting":[108],"frames":[109],"it":[110],"already":[111,176],"has.":[112],"Such":[113],"data-side":[114],"fixes,":[115],"however,":[116],"leave":[117],"policy's":[119],"per-frame":[120],"view":[121,214],"untouched:":[122],"single":[124],"image":[125],"still":[126],"maps":[127],"directly":[128],"an":[130,154],"action,":[131],"local":[134],"that":[136,163],"governs":[137],"correction":[138],"stays":[139],"implicit.":[140],"therefore":[142],"turn":[143],"representation":[146],"level":[147],"introduce":[149],"STAIR":[150,190],"(\\textbf{S}patio-\\textbf{T}emporal":[151],"feature":[152,162],"\\textbf{A}s":[153],"\\textbf{I}nterface":[155],"\\textbf{R}obot":[157],"learning),":[158],"compact":[160],"dynamic":[161],"bridges":[164],"vision-language":[166],"model":[167],"action":[170],"expert,":[171],"distilling":[172],"short-horizon":[174],"recorded":[177],"in":[178],"each":[179],"trajectory":[180],"dense,":[182],"motion-aware":[183],"supervision.":[184],"Trained":[185],"on":[186],"alone,":[189],"recovers":[191],"most":[192],"deliberate-demonstration":[195],"($50.0$":[197],"$62.2\\%$":[199],"overall,":[200],"approaching":[201],"$64.4\\%$":[203],"deliberate":[205],"demonstrations).":[206],"These":[207],"results":[208],"call":[209],"more":[212],"pedagogical":[213],"data,":[217],"optimized":[218],"machine":[220],"learnability":[221],"rather":[222],"than":[223],"human":[224],"efficiency":[225],"alone.":[226]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-17T00:00:00"}
