{"id":"https://openalex.org/W7170895395","doi":"https://doi.org/10.48550/arxiv.2607.21582","title":"Scale Up Strategically: Learning Compositional Generalization via Bias-Aware Evaluation and Data Collection for Robotic Manipulation","display_name":"Scale Up Strategically: Learning Compositional Generalization via Bias-Aware Evaluation and Data Collection for Robotic Manipulation","publication_year":2026,"publication_date":"2026-07-23","ids":{"openalex":"https://openalex.org/W7170895395","doi":"https://doi.org/10.48550/arxiv.2607.21582"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.21582","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.21582","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.2607.21582","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5143545880","display_name":"Yu Qi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qi, Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5143552799","display_name":"Zhang Ye","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ye, Zhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103458235","display_name":"X X Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Xinyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085698173","display_name":"Ye Lu","orcid":"https://orcid.org/0000-0002-2376-4519"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Yuxuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5143569488","display_name":"Amitoj Sandhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sandhu, Amitoj","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5142958969","display_name":"B Z Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Boce","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5143596867","display_name":"Haojie Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Haojie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5143594468","display_name":"Jonathan Tremblay","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tremblay, Jonathan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5032791503","display_name":"Lawson L. S. Wong","orcid":"https://orcid.org/0000-0002-9944-7587"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wong, Lawson L. S.","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":0.6365000009536743,"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":0.6365000009536743,"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":0.15620000660419464,"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":0.06300000101327896,"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/generalization","display_name":"Generalization","score":0.6485999822616577},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.6026999950408936},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.5986999869346619},{"id":"https://openalex.org/keywords/hierarchy","display_name":"Hierarchy","score":0.5548999905586243},{"id":"https://openalex.org/keywords/factor","display_name":"Factor (programming language)","score":0.5494999885559082},{"id":"https://openalex.org/keywords/data-collection","display_name":"Data collection","score":0.5205000042915344},{"id":"https://openalex.org/keywords/learnability","display_name":"Learnability","score":0.4909999966621399},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.46779999136924744},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.4422000050544739}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6578999757766724},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6485999822616577},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6164000034332275},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.6026999950408936},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.5986999869346619},{"id":"https://openalex.org/C31170391","wikidata":"https://www.wikidata.org/wiki/Q188619","display_name":"Hierarchy","level":2,"score":0.5548999905586243},{"id":"https://openalex.org/C2781039887","wikidata":"https://www.wikidata.org/wiki/Q1391724","display_name":"Factor (programming language)","level":2,"score":0.5494999885559082},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.5205000042915344},{"id":"https://openalex.org/C2777723229","wikidata":"https://www.wikidata.org/wiki/Q4367921","display_name":"Learnability","level":2,"score":0.4909999966621399},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4733999967575073},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.46779999136924744},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.4422000050544739},{"id":"https://openalex.org/C2780735816","wikidata":"https://www.wikidata.org/wiki/Q28324931","display_name":"Incremental learning","level":2,"score":0.4268999993801117},{"id":"https://openalex.org/C151913843","wikidata":"https://www.wikidata.org/wiki/Q3454555","display_name":"Dominance (genetics)","level":3,"score":0.39719998836517334},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.3813000023365021},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.36079999804496765},{"id":"https://openalex.org/C2776397901","wikidata":"https://www.wikidata.org/wiki/Q24905","display_name":"Verb","level":2,"score":0.3181999921798706},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.2985999882221222},{"id":"https://openalex.org/C2775955345","wikidata":"https://www.wikidata.org/wiki/Q7449071","display_name":"Semantic mapping","level":2,"score":0.28700000047683716},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.2766999900341034},{"id":"https://openalex.org/C120968358","wikidata":"https://www.wikidata.org/wiki/Q2011845","display_name":"Object-orientation","level":3,"score":0.27489998936653137},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.274399995803833},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.26899999380111694},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.2639999985694885},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.2619999945163727},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.2619999945163727},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2581000030040741}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.21582","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.21582","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.2607.21582","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.21582","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Compositional":[0],"generalization":[1],"is":[2,129],"essential":[3],"for":[4],"robot":[5,152],"to":[6,15,19,35,63],"follow":[7],"diverse":[8],"instructions.":[9],"However,":[10],"pretrained":[11],"policies":[12,62,100],"are":[13],"known":[14],"take":[16],"shortcuts,":[17,69],"deferring":[18],"salient":[20],"cues":[21],"rather":[22],"than":[23],"grounding":[24],"language.":[25],"We":[26,124],"introduce":[27],"a":[28,93,131,138,150],"diagnostic":[29],"framework":[30,53],"that":[31,136],"localizes":[32],"this":[33],"failure":[34],"individual":[36],"\\textit{instruction":[37],"factors},":[38],"\\textit{e.g.,}":[39],"reusable":[40],"semantic":[41],"components":[42],"such":[43],"as":[44,68],"color,":[45],"verb,":[46],"object,":[47],"size,":[48,114],"and":[49,70,85,118,120,148,161],"spatial":[50,110],"attribute.":[51],"Our":[52],"formalizes":[54],"instruction":[55],"factor":[56],"bias,":[57],"the":[58,127,155],"tendency":[59],"of":[60],"fine-tuned":[61],"over-rely":[64],"on":[65,97,149],"dominant":[66],"factors":[67,143],"quantifies":[71],"it":[72],"through":[73],"two":[74],"metrics:":[75],"Factor":[76,86],"Dominance":[77,87],"Rate":[78],"(FDR),":[79],"capturing":[80],"pairwise":[81],"bias":[82],"between":[83],"factors,":[84],"Hierarchy":[88],"(FDH),":[89],"aggregating":[90],"these":[91],"into":[92],"global":[94],"ranking.":[95],"Evaluation":[96],"six":[98],"foundation":[99],"reveals":[101],"broadly":[102],"consistent":[103],"ordering,":[104],"\\textit{i.e.},":[105],"color":[106,116],"$\\geq$":[107,109,111,113],"object":[108],"verb":[112,119],"with":[115],"dominant,":[117],"size":[121],"most":[122],"under-grounded.":[123],"further":[125],"show":[126],"diagnosis":[128],"actionable:":[130],"bias-aware":[132],"data":[133],"collection":[134],"strategy":[135],"reallocates":[137],"fixed":[139],"budget":[140],"toward":[141],"under-grounded":[142],"outperforms":[144],"baselines":[145],"in":[146],"simulation":[147],"real":[151],"using":[153],"half":[154],"demonstrations,":[156],"thereby":[157],"enabling":[158],"more":[159],"sample-efficient":[160],"generalizable":[162],"policy":[163],"learning.":[164]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-25T00:00:00"}
