{"id":"https://openalex.org/W7140482348","doi":"https://doi.org/10.48550/arxiv.2603.23684","title":"MoCHA: Denoising Caption Supervision for Motion-Text Retrieval","display_name":"MoCHA: Denoising Caption Supervision for Motion-Text Retrieval","publication_year":2026,"publication_date":"2026-03-24","ids":{"openalex":"https://openalex.org/W7140482348","doi":"https://doi.org/10.48550/arxiv.2603.23684"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.23684","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.23684","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":"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.2603.23684","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5093367368","display_name":"Nikolai Warner","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Warner, Nikolai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130668640","display_name":"Cameron Ethan Taylor","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Taylor, Cameron Ethan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070348998","display_name":"Irfan Essa","orcid":"https://orcid.org/0000-0002-6236-2969"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Essa, Irfan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5070311779","display_name":"Apaar Sadhwani","orcid":"https://orcid.org/0000-0002-9272-2574"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sadhwani, Apaar","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/T12290","display_name":"Human Motion and Animation","score":0.6758999824523926,"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/T12290","display_name":"Human Motion and Animation","score":0.6758999824523926,"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":0.2248000055551529,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.03680000081658363,"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/preprocessor","display_name":"Preprocessor","score":0.695900022983551},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6833000183105469},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5856000185012817},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.5239999890327454},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.49309998750686646},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.4074999988079071},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.383899986743927},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.36570000648498535},{"id":"https://openalex.org/keywords/mixing","display_name":"Mixing (physics)","score":0.33640000224113464},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.3357999920845032}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7111999988555908},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.695900022983551},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6833000183105469},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5856000185012817},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5313000082969666},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.5239999890327454},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.49309998750686646},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4359999895095825},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.4074999988079071},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.383899986743927},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.36570000648498535},{"id":"https://openalex.org/C138777275","wikidata":"https://www.wikidata.org/wiki/Q6884054","display_name":"Mixing (physics)","level":2,"score":0.33640000224113464},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3357999920845032},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32429999113082886},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3221000134944916},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.32190001010894775},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.31360000371932983},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.3012999892234802},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.2851000130176544},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.2824000120162964},{"id":"https://openalex.org/C2776175482","wikidata":"https://www.wikidata.org/wiki/Q1195816","display_name":"Transfer (computing)","level":2,"score":0.2770000100135803},{"id":"https://openalex.org/C2983327147","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Image denoising","level":3,"score":0.2770000100135803},{"id":"https://openalex.org/C18653775","wikidata":"https://www.wikidata.org/wiki/Q1333358","display_name":"Joint probability distribution","level":2,"score":0.2768000066280365},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.2732999920845032},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.2721000015735626},{"id":"https://openalex.org/C2778152352","wikidata":"https://www.wikidata.org/wiki/Q5165061","display_name":"Content (measure theory)","level":2,"score":0.2718000113964081},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.27079999446868896},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.2623000144958496},{"id":"https://openalex.org/C122048520","wikidata":"https://www.wikidata.org/wiki/Q2913954","display_name":"Percentile","level":2,"score":0.25699999928474426},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.25459998846054077},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.25369998812675476},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.25290000438690186},{"id":"https://openalex.org/C167723999","wikidata":"https://www.wikidata.org/wiki/Q3773214","display_name":"Sampling distribution","level":2,"score":0.2513999938964844}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.23684","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.23684","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":"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.2603.23684","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.23684","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":"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":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.5943012237548828}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Text-motion":[0],"retrieval":[1,162],"systems":[2],"learn":[3],"shared":[4],"embedding":[5,80],"spaces":[6],"from":[7,24,57],"motion-caption":[8],"pairs":[9],"via":[10],"contrastive":[11,63],"objectives.":[12],"However,":[13],"each":[14,66,98],"caption":[15,67,99],"is":[16,115],"not":[17],"a":[18,22,25,88,116,143,156,170],"deterministic":[19,120],"label":[20],"but":[21],"sample":[23],"distribution":[26],"of":[27,173,205],"valid":[28],"descriptions:":[29],"different":[30,33],"annotators":[31],"produce":[32],"text":[34,89],"for":[35],"the":[36,69,174,183,199,237],"same":[37],"motion,":[38],"mixing":[39],"motion-recoverable":[40,102],"semantics":[41],"(action":[42],"type,":[43],"body":[44],"parts,":[45],"directionality)":[46],"with":[47,160,221],"annotator-specific":[48],"style":[49],"and":[50,77,111,142,180,193,207,216,228],"inferred":[51],"context":[52],"that":[53,82,92,235],"cannot":[54],"be":[55],"determined":[56],"3D":[58],"joint":[59],"coordinates":[60],"alone.":[61],"Standard":[62],"training":[64],"treats":[65],"as":[68,155],"single":[70],"positive":[71,109],"target,":[72],"overlooking":[73],"this":[74,94],"distributional":[75],"structure":[76],"inducing":[78],"within-motion":[79,211],"variance":[81,95,213],"weakens":[83],"alignment.":[84],"We":[85,133],"propose":[86],"MoCHA,":[87],"canonicalization":[90],"framework":[91],"reduces":[93,210],"by":[96,214,226,232],"projecting":[97],"onto":[100],"its":[101],"content":[103],"prior":[104],"to":[105,165,223,230],"encoding,":[106],"producing":[107],"tighter":[108],"clusters":[110],"better-separated":[112],"embeddings.":[113],"Canonicalization":[114,209],"general":[117],"principle:":[118],"even":[119],"rule-based":[121],"methods":[122],"improve":[123],"cross-dataset":[124,218],"transfer,":[125],"though":[126],"learned":[127,136],"canonicalizers":[128],"provide":[129],"substantially":[130],"larger":[131],"gains.":[132],"present":[134],"two":[135],"variants:":[137],"an":[138],"LLM-based":[139],"approach":[140],"(GPT-5.2)":[141],"distilled":[144],"FlanT5":[145],"model":[146],"requiring":[147],"no":[148],"LLM":[149,184],"at":[150],"inference":[151],"time.":[152],"MoCHA":[153,168],"operates":[154],"preprocessing":[157],"step":[158],"compatible":[159],"any":[161],"architecture.":[163],"Applied":[164],"MoPa":[166],"(MotionPatches),":[167],"sets":[169],"new":[171],"state":[172],"art":[175],"on":[176,190,195],"both":[177],"HumanML3D":[178],"(H)":[179],"KIT-ML":[181],"(K):":[182],"variant":[185,202],"achieves":[186,203],"13.9%":[187],"T2M":[188],"R@1":[189],"H":[191,222,231],"(+3.1pp)":[192],"24.3%":[194],"K":[196,224,229],"(+10.3pp),":[197],"while":[198],"LLM-free":[200],"T5":[201],"gains":[204],"+2.5pp":[206],"+8.1pp.":[208],"text-embedding":[212],"11-19%":[215],"improves":[217],"transfer":[219],"substantially,":[220],"improving":[225],"94%":[227],"52%,":[233],"demonstrating":[234],"standardizing":[236],"language":[238],"space":[239],"yields":[240],"more":[241],"transferable":[242],"motion-language":[243],"representations.":[244]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-03-27T00:00:00"}
