{"id":"https://openalex.org/W4411113552","doi":"https://doi.org/10.18653/v1/2024.inlg-main.24","title":"Text2Traj2Text: Learning-by-Synthesis Framework for Contextual Captioning of Human Movement Trajectories","display_name":"Text2Traj2Text: Learning-by-Synthesis Framework for Contextual Captioning of Human Movement Trajectories","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4411113552","doi":"https://doi.org/10.18653/v1/2024.inlg-main.24"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2024.inlg-main.24","doi":"https://doi.org/10.18653/v1/2024.inlg-main.24","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2024.inlg-main.24","pdf_url":"https://aclanthology.org/2024.inlg-main.24.pdf","source":{"id":"https://openalex.org/S4306419715","display_name":"International Conference on Natural Language Generation","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th International Natural Language Generation Conference","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://aclanthology.org/2024.inlg-main.24.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5055248161","display_name":"Hikaru Asano","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210110652","display_name":"RIKEN","ror":"https://ror.org/01sjwvz98","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210110652"]},{"id":"https://openalex.org/I4210126580","display_name":"RIKEN Center for Advanced Intelligence Project","ror":"https://ror.org/03ckxwf91","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210110652","https://openalex.org/I4210126580"]},{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hikaru Asano","raw_affiliation_strings":["RIKEN AIP","The University of Tokyo"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"RIKEN AIP","institution_ids":["https://openalex.org/I4210110652","https://openalex.org/I4210126580"]},{"raw_affiliation_string":"The University of Tokyo","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020282208","display_name":"Ryo Yonetani","orcid":"https://orcid.org/0000-0002-2724-6233","observed_orcids":["https://orcid.org/0000-0002-2724-6233"]},"institutions":[{"id":"https://openalex.org/I4210089607","display_name":"CyberAgent (Japan)","ror":"https://ror.org/0060jg679","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210089607"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ryo Yonetani","raw_affiliation_strings":["CyberAgent Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CyberAgent Inc","institution_ids":["https://openalex.org/I4210089607"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076468808","display_name":"Taiki Sekii","orcid":"https://orcid.org/0000-0002-1895-3075","observed_orcids":["https://orcid.org/0000-0002-1895-3075"]},"institutions":[{"id":"https://openalex.org/I4210089607","display_name":"CyberAgent (Japan)","ror":"https://ror.org/0060jg679","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210089607"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Taiki Sekii","raw_affiliation_strings":["CyberAgent Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CyberAgent Inc","institution_ids":["https://openalex.org/I4210089607"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109372838","display_name":"Hiroki Ouchi","orcid":"https://orcid.org/0009-0006-5676-8950","observed_orcids":["https://orcid.org/0009-0006-5676-8950"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hiroki Ouchi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.355393,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"289","last_page":"302"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.7401999831199646,"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"}},"topics":[{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.7401999831199646,"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/T10028","display_name":"Topic Modeling","score":0.05090000107884407,"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/T11106","display_name":"Data Management and Algorithms","score":0.038100000470876694,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/large-language-models","display_name":"large language models","score":0.7820000052452087},{"id":"https://openalex.org/keywords/retail-stores","display_name":"retail stores","score":0.9190000295639038},{"id":"https://openalex.org/keywords/synthetic-trajectory-generation","display_name":"synthetic trajectory generation","score":0.6050000190734863},{"id":"https://openalex.org/keywords/customer-understanding","display_name":"customer understanding","score":0.531000018119812},{"id":"https://openalex.org/keywords/targeted-advertising","display_name":"targeted advertising","score":0.8500000238418579},{"id":"https://openalex.org/keywords/inventory-management","display_name":"inventory management","score":0.968999981880188}],"concepts":[{"id":"https://openalex.org/C157657479","wikidata":"https://www.wikidata.org/wiki/Q2367247","display_name":"Closed captioning","level":3,"score":0.961385190486908},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.763568639755249},{"id":"https://openalex.org/C2780226923","wikidata":"https://www.wikidata.org/wiki/Q929848","display_name":"Movement (music)","level":2,"score":0.7205681800842285},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4913994073867798},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4272611141204834},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.41260480880737305},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.4095747470855713},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3823385238647461},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.06314757466316223},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C107038049","wikidata":"https://www.wikidata.org/wiki/Q35986","display_name":"Aesthetics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.18653/v1/2024.inlg-main.24","doi":"https://doi.org/10.18653/v1/2024.inlg-main.24","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2024.inlg-main.24","pdf_url":"https://aclanthology.org/2024.inlg-main.24.pdf","source":{"id":"https://openalex.org/S4306419715","display_name":"International Conference on Natural Language Generation","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th International Natural Language Generation Conference","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2409.12670","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2409.12670","pdf_url":"https://arxiv.org/pdf/2409.12670","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,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2409.12670","doi":"https://doi.org/10.48550/arxiv.2409.12670","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2409.12670","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,"listed_in":[],"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"}],"best_oa_location":{"id":"doi:10.18653/v1/2024.inlg-main.24","doi":"https://doi.org/10.18653/v1/2024.inlg-main.24","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2024.inlg-main.24","pdf_url":"https://aclanthology.org/2024.inlg-main.24.pdf","source":{"id":"https://openalex.org/S4306419715","display_name":"International Conference on Natural Language Generation","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th International Natural Language Generation Conference","raw_type":"proceedings-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4411113552.pdf","grobid_xml":"https://content.openalex.org/works/W4411113552.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4417296426","https://openalex.org/W4416749668","https://openalex.org/W7038657298","https://openalex.org/W4415065637","https://openalex.org/W6922633372","https://openalex.org/W7166806951","https://openalex.org/W7214727161","https://openalex.org/W4417296462","https://openalex.org/W7164552209","https://openalex.org/W7166291020"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"Text2Traj2Text,":[3],"a":[4,46,62],"novel":[5],"learning-by-synthesis":[6],"framework":[7,91],"for":[8],"captioning":[9,71],"possible":[10],"contexts":[11],"behind":[12],"shopper's":[13],"trajectory":[14],"data":[15],"in":[16,95],"retail":[17,23],"stores.Our":[18],"work":[19],"will":[20],"impact":[21],"various":[22],"applications":[24],"that":[25],"need":[26],"better":[27],"customer":[28],"understanding,":[29],"such":[30],"as":[31,54,56],"targeted":[32],"advertising":[33],"and":[34,48,99],"inventory":[35],"management.The":[36],"key":[37],"idea":[38],"is":[39],"leveraging":[40],"large":[41],"language":[42],"models":[43],"to":[44,76],"synthesize":[45],"diverse":[47],"realistic":[49],"collection":[50],"of":[51,88,97],"contextual":[52],"captions":[53],"well":[55,75],"the":[57,70,86,89],"corresponding":[58],"movement":[59],"trajectories":[60],"on":[61],"store":[63],"map.Despite":[64],"learned":[65],"from":[66],"fully":[67],"synthesized":[68],"data,":[69],"model":[72],"can":[73],"generalize":[74],"trajectories/captions":[77],"created":[78],"by":[79],"real":[80],"human":[81],"subjects.Our":[82],"systematic":[83],"evaluation":[84],"confirmed":[85],"effectiveness":[87],"proposed":[90],"over":[92],"competitive":[93],"approaches":[94],"terms":[96],"ROUGE":[98],"BERT":[100],"Score":[101],"metrics.":[102]},"counts_by_year":[],"updated_date":"2026-10-30T12:39:25.321706","created_date":"2025-10-10T00:00:00"}
