{"id":"https://openalex.org/W7139910721","doi":"https://doi.org/10.48550/arxiv.2603.18453","title":"Learning Consistent Temporal Grounding between Related Tasks in Sports Coaching","display_name":"Learning Consistent Temporal Grounding between Related Tasks in Sports Coaching","publication_year":2026,"publication_date":"2026-03-19","ids":{"openalex":"https://openalex.org/W7139910721","doi":"https://doi.org/10.48550/arxiv.2603.18453"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.18453","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.18453","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":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.2603.18453","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037312803","display_name":"Arushi Rai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rai, Arushi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5072882318","display_name":"Adriana Kovashka","orcid":"https://orcid.org/0000-0003-1901-9660"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kovashka, Adriana","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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.23639999330043793,"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"}},"topics":[{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.23639999330043793,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.18150000274181366,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.11249999701976776,"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/coaching","display_name":"Coaching","score":0.7271999716758728},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.49939998984336853},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.4763000011444092},{"id":"https://openalex.org/keywords/task-analysis","display_name":"Task analysis","score":0.3197000026702881},{"id":"https://openalex.org/keywords/athletes","display_name":"Athletes","score":0.298799991607666},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.28619998693466187}],"concepts":[{"id":"https://openalex.org/C2779363792","wikidata":"https://www.wikidata.org/wiki/Q1104185","display_name":"Coaching","level":2,"score":0.7271999716758728},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5497999787330627},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.49939998984336853},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.4763000011444092},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.44940000772476196},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.43459999561309814},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42179998755455017},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.41290000081062317},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.3197000026702881},{"id":"https://openalex.org/C2781054738","wikidata":"https://www.wikidata.org/wiki/Q4813730","display_name":"Athletes","level":2,"score":0.298799991607666},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2921999990940094},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.28619998693466187},{"id":"https://openalex.org/C168993435","wikidata":"https://www.wikidata.org/wiki/Q6501125","display_name":"Ground","level":2,"score":0.27390000224113464},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2703000009059906},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2702000141143799},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.2596000134944916},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.2572999894618988},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2515999972820282}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.18453","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.18453","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":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.2603.18453","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.18453","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":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":{"Video-LLMs":[0],"often":[1],"attend":[2,54],"to":[3,25,55],"irrelevant":[4],"frames,":[5],"which":[6,76],"is":[7,22,87],"especially":[8],"detrimental":[9],"for":[10],"sports":[11,113],"coaching":[12,114],"tasks":[13],"requiring":[14],"precise":[15],"temporal":[16,36],"grounding.":[17],"Yet":[18],"obtaining":[19],"frame-level":[20],"supervision":[21],"challenging:":[23],"expensive":[24],"collect":[26],"from":[27,31],"humans":[28],"and":[29,51,105,118],"unreliable":[30],"other":[32],"models.":[33,123],"We":[34,59,91],"improve":[35],"grounding":[37],"without":[38],"additional":[39],"annotations":[40],"by":[41],"exploiting":[42],"the":[43,56],"observation":[44],"that":[45,84,94],"related":[46],"tasks,":[47],"such":[48],"as":[49],"generation":[50],"verification,":[52],"must":[53],"same":[57],"frames.":[58],"enforce":[60],"this":[61],"via":[62],"a":[63,88],"self-consistency":[64],"objective":[65,98],"over":[66,108],"select":[67],"visual":[68],"attention":[69,85],"maps":[70],"of":[71,101],"tightly-related":[72],"tasks.":[73],"Using":[74],"VidDiffBench,":[75],"provides":[77],"ground-truth":[78],"keyframe":[79],"annotations,":[80],"we":[81],"first":[82],"validate":[83],"misallocation":[86],"significant":[89],"bottleneck.":[90],"then":[92],"show":[93],"training":[95],"with":[96],"our":[97],"yields":[99],"gains":[100],"+3.0%,":[102],"+14.1%":[103],"accuracy":[104],"+0.9":[106],"BERTScore":[107],"supervised":[109],"finetuning":[110],"across":[111],"three":[112],"tasks:":[115],"Exact,":[116],"FitnessQA,":[117],"ExpertAF,":[119],"even":[120],"surpassing":[121],"closed-source":[122]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-21T00:00:00"}