{"id":"https://openalex.org/W7169063566","doi":"https://doi.org/10.48550/arxiv.2607.13461","title":"Joint On-and-Off Policy Learning for Vision-and-Language Navigation","display_name":"Joint On-and-Off Policy Learning for Vision-and-Language Navigation","publication_year":2026,"publication_date":"2026-07-15","ids":{"openalex":"https://openalex.org/W7169063566","doi":"https://doi.org/10.48550/arxiv.2607.13461"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.13461","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.13461","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.2607.13461","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101342709","display_name":"Qingrong He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Qingrong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140982905","display_name":"Lin Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Lin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5141026625","display_name":"Kevin Zheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Kevin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5110853658","display_name":"L C-C Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Liang","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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9758999943733215,"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":0.9758999943733215,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.0035000001080334187,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.002899999963119626,"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/imitation","display_name":"Imitation","score":0.5791000127792358},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5378000140190125},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5328999757766724},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.4884999990463257},{"id":"https://openalex.org/keywords/grasp","display_name":"GRASP","score":0.4699999988079071},{"id":"https://openalex.org/keywords/sorting","display_name":"Sorting","score":0.40290001034736633},{"id":"https://openalex.org/keywords/embodied-cognition","display_name":"Embodied cognition","score":0.384799987077713},{"id":"https://openalex.org/keywords/structured-prediction","display_name":"Structured prediction","score":0.3416999876499176},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.32690000534057617}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6959999799728394},{"id":"https://openalex.org/C126388530","wikidata":"https://www.wikidata.org/wiki/Q1131737","display_name":"Imitation","level":2,"score":0.5791000127792358},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5378000140190125},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5328999757766724},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5231999754905701},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.4884999990463257},{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.4699999988079071},{"id":"https://openalex.org/C111696304","wikidata":"https://www.wikidata.org/wiki/Q2303697","display_name":"Sorting","level":2,"score":0.40290001034736633},{"id":"https://openalex.org/C100609095","wikidata":"https://www.wikidata.org/wiki/Q1335050","display_name":"Embodied cognition","level":2,"score":0.384799987077713},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37459999322891235},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.35659998655319214},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.3416999876499176},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.32690000534057617},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.3230000138282776},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.3212999999523163},{"id":"https://openalex.org/C40506919","wikidata":"https://www.wikidata.org/wiki/Q7452469","display_name":"Sequence learning","level":2,"score":0.3199999928474426},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.31709998846054077},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.31630000472068787},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.2865999937057495},{"id":"https://openalex.org/C188888258","wikidata":"https://www.wikidata.org/wiki/Q7353390","display_name":"Robot learning","level":4,"score":0.28610000014305115},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.27889999747276306},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.2727999985218048},{"id":"https://openalex.org/C132758656","wikidata":"https://www.wikidata.org/wiki/Q5307365","display_name":"Dreyfus model of skill acquisition","level":2,"score":0.2685000002384186},{"id":"https://openalex.org/C2779231336","wikidata":"https://www.wikidata.org/wiki/Q7534724","display_name":"Sketch","level":2,"score":0.2678000032901764},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.2639999985694885},{"id":"https://openalex.org/C2781002164","wikidata":"https://www.wikidata.org/wiki/Q6822311","display_name":"Meta learning (computer science)","level":3,"score":0.26019999384880066}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.13461","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.13461","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.2607.13461","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.13461","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":0.43136462569236755}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Vision-and-Language":[0],"Navigation":[1],"(VLN)":[2],"necessitates":[3],"an":[4,158],"embodied":[5],"agent":[6],"to":[7,15,51,64,111,122,134,152],"navigate":[8],"in":[9,21],"the":[10,27,46,73,117,170,182],"physical":[11],"world":[12],"by":[13,45,61],"adhering":[14],"natural":[16],"language":[17],"instructions.":[18],"Recent":[19],"advancements":[20],"Vision-Language":[22],"Models":[23],"(VLM)":[24],"have":[25],"propelled":[26],"development":[28],"of":[29,75,172,177],"VLM-based":[30],"VLN":[31,88],"methods":[32],"with":[33],"two":[34,79],"predominant":[35],"paradigms:":[36],"(1)":[37],"imitation":[38,94,132],"learning":[39,58,95,133,144],"(IL)":[40],"on":[41,108,181,193],"expert":[42,109],"demonstrations,":[43],"followed":[44],"Dataset":[47],"Aggregation":[48],"(DAgger)":[49],"algorithm":[50,119],"bolster":[52],"error":[53,136,165],"recovery":[54,137],"capabilities;":[55],"(2)":[56],"reinforcement":[57],"(RL)":[59],"driven":[60],"verifiable":[62],"rewards":[63],"enhance":[65,153],"reasoning":[66],"and":[67,96,157,179,185],"exploration.":[68],"A":[69],"notable":[70],"gap":[71],"is":[72,106,120,146],"absence":[74],"integration":[76],"between":[77],"these":[78],"distinct":[80],"paradigms.":[81],"This":[82],"paper":[83],"introduces":[84],"JOP-VLN,":[85,173],"a":[86,100,140,190],"novel":[87],"framework":[89,145],"that":[90],"synergistically":[91],"combines":[92],"off-policy":[93],"on-policy":[97],"exploration":[98,125],"within":[99],"three-stage":[101],"training":[102,155],"pipeline.":[103],"Initially,":[104],"IL":[105],"employed":[107],"demonstrations":[110],"acquire":[112],"basic":[113],"navigation":[114],"skills.":[115],"Subsequently,":[116],"DAgger":[118],"utilized":[121],"generate":[123],"heuristic":[124],"trajectories,":[126],"which":[127],"are":[128],"then":[129],"used":[130],"for":[131,163],"improve":[135],"capabilities.":[138],"Finally,":[139],"joint":[141],"on-and-off":[142],"policy":[143],"implemented,":[147],"featuring":[148],"high-entropy":[149],"trajectory":[150,160],"sampling":[151],"RL":[154],"efficiency":[156],"error-correction-prioritized":[159],"sorting":[161],"strategy":[162],"effective":[164],"correction.":[166],"Extensive":[167],"experiments":[168],"demonstrate":[169],"efficacy":[171],"achieving":[174],"success":[175],"rates":[176],"69.9%":[178],"68.0%":[180],"VLN-CE":[183],"R2R":[184],"RxR":[186],"benchmarks,":[187],"respectively,":[188],"setting":[189],"new":[191],"state-of-the-art":[192],"R2R.":[194],"Project":[195],"page:":[196],"https://qingrongh.github.io/JOP-VLN.":[197]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-17T00:00:00"}