{"id":"https://openalex.org/W4283787995","doi":"https://doi.org/10.1109/tnnls.2022.3183287","title":"Vision\u2013Language Navigation With Beam-Constrained Global Normalization","display_name":"Vision\u2013Language Navigation With Beam-Constrained Global Normalization","publication_year":2022,"publication_date":"2022-07-01","ids":{"openalex":"https://openalex.org/W4283787995","doi":"https://doi.org/10.1109/tnnls.2022.3183287","pmid":"https://pubmed.ncbi.nlm.nih.gov/35776817"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2022.3183287","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3183287","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5009285282","display_name":"Liang Xie","orcid":"https://orcid.org/0000-0002-8286-6785"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Liang Xie","raw_affiliation_strings":["Academy of Military Sciences China, National Innovation Institute of Defense Technology, Beijing, China","Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Academy of Military Sciences China, National Innovation Institute of Defense Technology, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004953265","display_name":"Meishan Zhang","orcid":"https://orcid.org/0000-0001-6335-1340"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]},{"id":"https://openalex.org/I158809036","display_name":"Shenzhen Institute of Information Technology","ror":"https://ror.org/03wrf9427","country_code":"CN","type":"education","lineage":["https://openalex.org/I158809036"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meishan Zhang","raw_affiliation_strings":["Institute of Computing and Intelligence, Harbin Institute of Technology (Shenzhen), Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Institute of Computing and Intelligence, Harbin Institute of Technology (Shenzhen), Shenzhen, China","institution_ids":["https://openalex.org/I158809036","https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100401819","display_name":"You Li","orcid":"https://orcid.org/0000-0002-0152-1655"},"institutions":[{"id":"https://openalex.org/I4210163738","display_name":"China Astronaut Research and Training Center","ror":"https://ror.org/001ycj259","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210163738"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"You Li","raw_affiliation_strings":["National Key Laboratory of Human Factors Engineering, China Astronaut Research and Training Center, Beijing, China"],"affiliations":[{"raw_affiliation_string":"National Key Laboratory of Human Factors Engineering, China Astronaut Research and Training Center, Beijing, China","institution_ids":["https://openalex.org/I4210163738"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030329860","display_name":"Qin Wei","orcid":"https://orcid.org/0000-0002-3034-8046"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei Qin","raw_affiliation_strings":["Academy of Military Sciences China, National Innovation Institute of Defense Technology, Beijing, China","Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Academy of Military Sciences China, National Innovation Institute of Defense Technology, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100425119","display_name":"Ye Yan","orcid":"https://orcid.org/0000-0002-7514-0505"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ye Yan","raw_affiliation_strings":["Academy of Military Sciences China, National Innovation Institute of Defense Technology, Beijing, China","Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Academy of Military Sciences China, National Innovation Institute of Defense Technology, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071229482","display_name":"Erwei Yin","orcid":"https://orcid.org/0000-0002-2147-9888"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Erwei Yin","raw_affiliation_strings":["Academy of Military Sciences China, National Innovation Institute of Defense Technology, Beijing, China","Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Academy of Military Sciences China, National Innovation Institute of Defense Technology, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5009285282"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7043,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.69647782,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"35","issue":"1","first_page":"1352","last_page":"1363"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":1.0,"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":1.0,"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":0.9972000122070312,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.988099992275238,"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/computer-science","display_name":"Computer science","score":0.7180060148239136},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.6715938448905945},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6254939436912537},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.6119365096092224},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5478923916816711},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.5021882057189941},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4576718807220459},{"id":"https://openalex.org/keywords/beam-search","display_name":"Beam search","score":0.4425998032093048},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4207918047904968},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3976505696773529},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.23169028759002686},{"id":"https://openalex.org/keywords/search-algorithm","display_name":"Search algorithm","score":0.09450176358222961}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7180060148239136},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.6715938448905945},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6254939436912537},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.6119365096092224},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5478923916816711},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.5021882057189941},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4576718807220459},{"id":"https://openalex.org/C19889080","wikidata":"https://www.wikidata.org/wiki/Q2835852","display_name":"Beam search","level":3,"score":0.4425998032093048},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4207918047904968},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3976505696773529},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.23169028759002686},{"id":"https://openalex.org/C125583679","wikidata":"https://www.wikidata.org/wiki/Q755673","display_name":"Search algorithm","level":2,"score":0.09450176358222961},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2022.3183287","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3183287","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:35776817","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35776817","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.6200000047683716}],"awards":[{"id":"https://openalex.org/G2078206887","display_name":null,"funder_award_id":"61901505","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6199636763","display_name":null,"funder_award_id":"62076250","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7456101303","display_name":null,"funder_award_id":"61703407","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W15592790","https://openalex.org/W639708223","https://openalex.org/W1931639407","https://openalex.org/W1933349210","https://openalex.org/W2118781169","https://openalex.org/W2121127625","https://openalex.org/W2161222299","https://openalex.org/W2189089430","https://openalex.org/W2194775991","https://openalex.org/W2236233024","https://openalex.org/W2250451826","https://openalex.org/W2516334389","https://openalex.org/W2745461083","https://openalex.org/W2805984364","https://openalex.org/W2886095922","https://openalex.org/W2926977875","https://openalex.org/W2951973805","https://openalex.org/W2962744691","https://openalex.org/W2962887844","https://openalex.org/W2963162313","https://openalex.org/W2963463964","https://openalex.org/W2963572611","https://openalex.org/W2963620441","https://openalex.org/W2963800628","https://openalex.org/W2964339842","https://openalex.org/W2964935470","https://openalex.org/W2967186499","https://openalex.org/W2967853831","https://openalex.org/W2970231061","https://openalex.org/W3034500398","https://openalex.org/W3035640828","https://openalex.org/W3105521436","https://openalex.org/W3106571068","https://openalex.org/W3107069568","https://openalex.org/W3109085430","https://openalex.org/W3109097593","https://openalex.org/W6679961713","https://openalex.org/W6682082992","https://openalex.org/W6682691769","https://openalex.org/W6695909211","https://openalex.org/W6719057275","https://openalex.org/W6728274705","https://openalex.org/W6729856301","https://openalex.org/W6731334075","https://openalex.org/W6739901393","https://openalex.org/W6744863947","https://openalex.org/W6757724268","https://openalex.org/W6766904570","https://openalex.org/W6770103389","https://openalex.org/W6784287907"],"related_works":["https://openalex.org/W4386269615","https://openalex.org/W2591697403","https://openalex.org/W2944728705","https://openalex.org/W2904022177","https://openalex.org/W2359348847","https://openalex.org/W3011538607","https://openalex.org/W4294432981","https://openalex.org/W4307932641","https://openalex.org/W2903036216","https://openalex.org/W2088056149"],"abstract_inverted_index":{"Vision-language":[0],"navigation":[1,37],"(VLN)":[2],"is":[3,23,96,200],"a":[4,14,40,82,97,123,133],"challenging":[5],"task,":[6,32],"which":[7,33],"guides":[8],"an":[9],"agent":[10,36],"to":[11,51,137,152,187],"navigate":[12],"in":[13,68,156,161],"realistic":[15],"environment":[16],"by":[17,39,77,122],"natural":[18],"language":[19],"instructions.":[20],"Sequence-to-sequence":[21],"modeling":[22],"one":[24],"of":[25,42,47,100,104,185],"the":[26,31,35,52,60,64,85,105,139,142,157,169,180,192,196,206,217],"most":[27],"prospective":[28],"architectures":[29],"for":[30],"achieves":[34],"goal":[38],"sequence":[41],"moving":[43],"actions.":[44],"The":[45,94],"line":[46],"work":[48],"has":[49],"led":[50],"state-of-the-art":[53],"performance.":[54],"Recently,":[55],"several":[56],"studies":[57],"showed":[58],"that":[59,195],"beam-search":[61],"decoding":[62],"during":[63,92],"inference":[65],"can":[66,172,212],"result":[67],"promising":[69],"performance,":[70],"as":[71,81],"it":[72],"ranks":[73],"multiple":[74],"candidate":[75],"trajectories":[76,117],"scoring":[78],"each":[79],"trajectory":[80,143,164],"whole.":[83],"However,":[84],"trajectory-level":[86],"score":[87,95,150],"might":[88],"be":[89,113,173],"seriously":[90],"biased":[91],"ranking.":[93],"simple":[98],"averaging":[99],"individual":[101],"unit":[102,110],"scores":[103,111,140],"target-sequence":[106],"actions,":[107],"and":[108,191],"these":[109],"could":[112],"incomparable":[114],"among":[115],"different":[116],"since":[118],"they":[119],"are":[120],"calculated":[121],"local":[124],"discriminant":[125],"classifier.":[126],"To":[127],"address":[128],"this":[129,167],"problem,":[130],"we":[131,146],"propose":[132],"global":[134,149,198],"normalization":[135],"strategy":[136],"rescale":[138],"at":[141],"level.":[144],"Concretely,":[145],"present":[147],"two":[148],"functions":[151],"rerank":[153],"all":[154],"candidates":[155],"output":[158],"beam,":[159],"resulting":[160],"more":[162],"comparable":[163],"scores.":[165],"In":[166],"way,":[168],"bias":[170],"problem":[171],"greatly":[174],"alleviated.":[175],"We":[176],"conduct":[177],"experiments":[178],"on":[179,216],"benchmark":[181],"room-to-room":[182],"(R2R)":[183],"dataset":[184],"VLN":[186,218],"verify":[188],"our":[189],"method,":[190],"results":[193],"show":[194],"proposed":[197],"method":[199],"effective,":[201],"providing":[202],"significant":[203],"performance":[204,215],"than":[205],"corresponding":[207],"baselines.":[208],"Our":[209],"final":[210],"model":[211],"achieve":[213],"competitive":[214],"leaderboard.":[219]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
