{"id":"https://openalex.org/W7207572021","doi":"https://doi.org/10.18653/2026.emnlp-main.239","title":"LookStep: Efficient Vision-Language Navigation with Linguistic Foresight and Event Driven Memory","display_name":"LookStep: Efficient Vision-Language Navigation with Linguistic Foresight and Event Driven Memory","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7207572021","doi":"https://doi.org/10.18653/2026.emnlp-main.239"},"language":"en","primary_location":{"id":"doi:10.18653/2026.emnlp-main.239","doi":"https://doi.org/10.18653/2026.emnlp-main.239","is_oa":true,"landing_page_url":"https://doi.org/10.18653/2026.emnlp-main.239","pdf_url":"https://aclanthology.org/2026.emnlp-main.239.pdf","source":{"id":"https://openalex.org/S4363608991","display_name":"Conference on Empirical Methods in Natural Language Processing (EMNLP)","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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://aclanthology.org/2026.emnlp-main.239.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130652240","display_name":"Kun-Yang Yu","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kun-Yang Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124914493","display_name":"Yingzhe Li","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingzhe Li","raw_affiliation_strings":["National Key Laboratory for Novel Software Technology , Nanjing University","School of Artificial Intelligence , Nanjing University","TermiTech"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory for Novel Software Technology , Nanjing University","institution_ids":["https://openalex.org/I881766915"]},{"raw_affiliation_string":"School of Artificial Intelligence , Nanjing University","institution_ids":["https://openalex.org/I881766915"]},{"raw_affiliation_string":"TermiTech","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122515545","display_name":"Hongyu Xu","orcid":"https://orcid.org/0009-0001-7132-5078","observed_orcids":["https://orcid.org/0009-0001-7132-5078"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hongyu Xu","raw_affiliation_strings":["TermiTech"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TermiTech","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130649096","display_name":"Shi-Yu Tian","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shi-Yu Tian","raw_affiliation_strings":["National Key Laboratory for Novel Software Technology , Nanjing University","School of Artificial Intelligence , Nanjing University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory for Novel Software Technology , Nanjing University","institution_ids":["https://openalex.org/I881766915"]},{"raw_affiliation_string":"School of Artificial Intelligence , Nanjing University","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136049471","display_name":"Zhi Zhou","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhi Zhou","raw_affiliation_strings":["National Key Laboratory for Novel Software Technology , Nanjing University","School of Artificial Intelligence , Nanjing University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory for Novel Software Technology , Nanjing University","institution_ids":["https://openalex.org/I881766915"]},{"raw_affiliation_string":"School of Artificial Intelligence , Nanjing University","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5149689687","display_name":"Yang Chen","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Chen","raw_affiliation_strings":["National Key Laboratory for Novel Software Technology , Nanjing University","School of Intelligence Science and Technology , Nanjing University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory for Novel Software Technology , Nanjing University","institution_ids":["https://openalex.org/I881766915"]},{"raw_affiliation_string":"School of Intelligence Science and Technology , Nanjing University","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133611099","display_name":"Ming Yang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Yang","raw_affiliation_strings":["National Key Laboratory for Novel Software Technology , Nanjing University","School of Artificial Intelligence , Nanjing University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory for Novel Software Technology , Nanjing University","institution_ids":["https://openalex.org/I881766915"]},{"raw_affiliation_string":"School of Artificial Intelligence , Nanjing University","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133628007","display_name":"Sheng Wang","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sheng Wang","raw_affiliation_strings":["TermiTech"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TermiTech","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5149872847","display_name":"Qing Yu","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qing Yu","raw_affiliation_strings":["TermiTech"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TermiTech","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130197296","display_name":"Lan-Zhe Guo","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lan-Zhe Guo","raw_affiliation_strings":["National Key Laboratory for Novel Software Technology , Nanjing University","School of Intelligence Science and Technology , Nanjing University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory for Novel Software Technology , Nanjing University","institution_ids":["https://openalex.org/I881766915"]},{"raw_affiliation_string":"School of Intelligence Science and Technology , Nanjing University","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5130633883","display_name":"Yu-Feng Li","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu-Feng Li","raw_affiliation_strings":["National Key Laboratory for Novel Software Technology , Nanjing University","School of Artificial Intelligence , Nanjing University","TermiTech"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory for Novel Software Technology , Nanjing University","institution_ids":["https://openalex.org/I881766915"]},{"raw_affiliation_string":"School of Artificial Intelligence , Nanjing University","institution_ids":["https://openalex.org/I881766915"]},{"raw_affiliation_string":"TermiTech","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"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":0.61481721,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5465","last_page":"5483"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9580000042915344,"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":0.9580000042915344,"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":0.010599999688565731,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.006000000052154064,"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/vision-and-language-navigation","display_name":"vision-and-language navigation","score":0.9990000128746033},{"id":"https://openalex.org/keywords/natural-language-instructions","display_name":"natural language instructions","score":0.7609999775886536},{"id":"https://openalex.org/keywords/memory-efficiency","display_name":"memory efficiency","score":0.7310000061988831},{"id":"https://openalex.org/keywords/unknown-environments","display_name":"unknown environments","score":0.6060000061988831},{"id":"https://openalex.org/keywords/embodied-agents","display_name":"embodied agents","score":0.5189999938011169}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7947999835014343},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5667999982833862},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5073000192642212},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.49459999799728394},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.453900009393692},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4350999891757965},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.42410001158714294},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3707999885082245},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.3652999997138977},{"id":"https://openalex.org/C64848388","wikidata":"https://www.wikidata.org/wiki/Q188867","display_name":"Futures studies","level":2,"score":0.3626999855041504},{"id":"https://openalex.org/C12186640","wikidata":"https://www.wikidata.org/wiki/Q6815743","display_name":"Memory model","level":3,"score":0.36070001125335693},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3359000086784363},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3091999888420105},{"id":"https://openalex.org/C100609095","wikidata":"https://www.wikidata.org/wiki/Q1335050","display_name":"Embodied cognition","level":2,"score":0.3050999939441681},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3012999892234802},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.2996000051498413},{"id":"https://openalex.org/C2776544517","wikidata":"https://www.wikidata.org/wiki/Q189447","display_name":"Unexpected events","level":2,"score":0.29190000891685486},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2793000042438507},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.2793000042438507},{"id":"https://openalex.org/C197914299","wikidata":"https://www.wikidata.org/wiki/Q18650","display_name":"Semantic memory","level":3,"score":0.2702000141143799},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.2612999975681305}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.18653/2026.emnlp-main.239","doi":"https://doi.org/10.18653/2026.emnlp-main.239","is_oa":true,"landing_page_url":"https://doi.org/10.18653/2026.emnlp-main.239","pdf_url":"https://aclanthology.org/2026.emnlp-main.239.pdf","source":{"id":"https://openalex.org/S4363608991","display_name":"Conference on Empirical Methods in Natural Language Processing (EMNLP)","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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2609.02350","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.02350","pdf_url":"https://arxiv.org/pdf/2609.02350","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2609.02350","doi":"https://doi.org/10.48550/arxiv.2609.02350","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2609.02350","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":"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"}],"best_oa_location":{"id":"doi:10.18653/2026.emnlp-main.239","doi":"https://doi.org/10.18653/2026.emnlp-main.239","is_oa":true,"landing_page_url":"https://doi.org/10.18653/2026.emnlp-main.239","pdf_url":"https://aclanthology.org/2026.emnlp-main.239.pdf","source":{"id":"https://openalex.org/S4363608991","display_name":"Conference on Empirical Methods in Natural Language Processing (EMNLP)","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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7207572021.pdf","grobid_xml":"https://content.openalex.org/works/W7207572021.grobid-xml"},"referenced_works_count":1,"referenced_works":["https://openalex.org/W7202188380"],"related_works":["https://openalex.org/W7214721891","https://openalex.org/W7162094295","https://openalex.org/W7221510544","https://openalex.org/W4398157060","https://openalex.org/W7083697494","https://openalex.org/W7147139544","https://openalex.org/W7166695133","https://openalex.org/W7171506604","https://openalex.org/W7222921121","https://openalex.org/W7213100115"],"abstract_inverted_index":{"Vision-Language":[0],"Navigation":[1],"(VLN)":[2],"requires":[3,38],"an":[4],"embodied":[5],"agent":[6],"to":[7,58,62,95,111],"follow":[8,26],"natural-language":[9],"instructions":[10],"in":[11],"unseen":[12],"environments.Recent":[13],"progress":[14,99],"has":[15],"been":[16],"largely":[17],"driven":[18],"by":[19],"Multimodal":[20],"Large":[21],"Language":[22,81],"Models":[23],"(MLLMs).Existing":[24],"methods":[25,132],"a":[27,39,75,116,121,139],"next-step":[28],"action":[29],"prediction":[30],"paradigm,":[31],"supervising":[32],"only":[33],"the":[34,134],"expert":[35],"action,":[36,106],"which":[37],"high":[40,63],"quantity":[41],"of":[42],"data":[43,152],"for":[44,103],"training.They":[45],"also":[46],"rely":[47],"on":[48,143],"cognitive":[49],"maps,":[50],"accumulated":[51],"historical":[52],"frames,":[53],"or":[54],"external":[55],"3D":[56],"tools":[57],"maintain":[59],"states,":[60],"leading":[61],"computational":[64],"and":[65,86,100,150],"memory":[66,119,148],"overhead.To":[67],"realize":[68],"resource":[69],"efficiency":[70,149],"VLN,":[71],"we":[72],"propose":[73],"Look-Step,":[74],"unified":[76],"end-to-end":[77],"framework":[78],"that":[79,91],"combines":[80],"Centric":[82],"Future":[83],"State":[84],"Modeling":[85],"Event":[87],"Driven":[88],"Rolling":[89],"Memory":[90],"uses":[92],"language":[93],"labels":[94],"generate":[96],"coarse-grained":[97],"navigation":[98],"future":[101],"states":[102],"each":[104,113],"candidate":[105],"while":[107],"autonomously":[108],"deciding":[109],"whether":[110],"write":[112],"observation":[114],"into":[115],"bounded":[117],"rolling":[118],"with":[120,146],"semantic":[122],"role.We":[123],"validate":[124],"LookStep":[125,129],"empirically.On":[126],"VLN-CE":[127],"tasks,":[128],"outperforms":[130],"existing":[131],"under":[133],"same":[135],"training":[136],"settings,":[137],"achieving":[138],"49.7%":[140],"success":[141],"rate":[142],"R2R-CE":[144],"Val-Unseen":[145],"better":[147],"less":[151],"usage.":[153]},"counts_by_year":[],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2026-09-04T00:00:00"}
