{"id":"https://openalex.org/W4361200045","doi":"https://doi.org/10.23919/icact56868.2023.10079273","title":"Improving Embodied Instruction Following with Deterministic Methods","display_name":"Improving Embodied Instruction Following with Deterministic Methods","publication_year":2023,"publication_date":"2023-02-19","ids":{"openalex":"https://openalex.org/W4361200045","doi":"https://doi.org/10.23919/icact56868.2023.10079273"},"language":"en","primary_location":{"id":"doi:10.23919/icact56868.2023.10079273","is_oa":false,"landing_page_url":"http://dx.doi.org/10.23919/icact56868.2023.10079273","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 25th International Conference on Advanced Communication Technology (ICACT)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"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/A5101856126","display_name":"Dahyun Kim","orcid":"https://orcid.org/0000-0003-0881-8651"},"institutions":[{"id":"https://openalex.org/I4210161052","display_name":"Korea University","ror":"https://ror.org/05m1gnk07","country_code":"JP","type":"education","lineage":["https://openalex.org/I4210161052"]},{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["JP","KR"],"is_corresponding":true,"raw_author_name":"Dahyun Kim","raw_affiliation_strings":["Korea University,Dept. of Electrical Engineering","Dept. of Electrical Engineering, Korea University"],"affiliations":[{"raw_affiliation_string":"Korea University,Dept. of Electrical Engineering","institution_ids":["https://openalex.org/I4210161052","https://openalex.org/I197347611"]},{"raw_affiliation_string":"Dept. of Electrical Engineering, Korea University","institution_ids":["https://openalex.org/I197347611"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101403699","display_name":"Yong-Ju Lee","orcid":"https://orcid.org/0000-0001-9308-233X"},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yong-Ju Lee","raw_affiliation_strings":["Electronics and Telecommunication Research Institute,Daejeon,Korea","Electronics and Telecommunication Research Institute, Daejeon, Korea"],"affiliations":[{"raw_affiliation_string":"Electronics and Telecommunication Research Institute,Daejeon,Korea","institution_ids":["https://openalex.org/I142401562"]},{"raw_affiliation_string":"Electronics and Telecommunication Research Institute, Daejeon, Korea","institution_ids":["https://openalex.org/I142401562"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101856126"],"corresponding_institution_ids":["https://openalex.org/I197347611","https://openalex.org/I4210161052"],"apc_list":null,"apc_paid":null,"fwci":0.123,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.3635725,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"424","last_page":"428"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9995999932289124,"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":0.9995999932289124,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9990000128746033,"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/T11439","display_name":"Video Analysis and Summarization","score":0.998199999332428,"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/margin","display_name":"Margin (machine learning)","score":0.8252025842666626},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.8179726600646973},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7898776531219482},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7013210654258728},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5992856621742249},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5614611506462097},{"id":"https://openalex.org/keywords/embodied-cognition","display_name":"Embodied cognition","score":0.5141432881355286},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.49836277961730957},{"id":"https://openalex.org/keywords/imitation","display_name":"Imitation","score":0.49204322695732117},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.46666139364242554},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07964891195297241}],"concepts":[{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.8252025842666626},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.8179726600646973},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7898776531219482},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7013210654258728},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5992856621742249},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5614611506462097},{"id":"https://openalex.org/C100609095","wikidata":"https://www.wikidata.org/wiki/Q1335050","display_name":"Embodied cognition","level":2,"score":0.5141432881355286},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.49836277961730957},{"id":"https://openalex.org/C126388530","wikidata":"https://www.wikidata.org/wiki/Q1131737","display_name":"Imitation","level":2,"score":0.49204322695732117},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.46666139364242554},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07964891195297241},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/icact56868.2023.10079273","is_oa":false,"landing_page_url":"http://dx.doi.org/10.23919/icact56868.2023.10079273","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 25th International Conference on Advanced Communication Technology (ICACT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.8100000023841858}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2156047221","https://openalex.org/W2974759213","https://openalex.org/W2998903229","https://openalex.org/W3034758614","https://openalex.org/W3040041096","https://openalex.org/W3046631013","https://openalex.org/W3173760279","https://openalex.org/W3173781631","https://openalex.org/W3198840025","https://openalex.org/W4214700710","https://openalex.org/W4285306713","https://openalex.org/W4287026640","https://openalex.org/W4293566037","https://openalex.org/W6747106673","https://openalex.org/W6780443396","https://openalex.org/W6781736217","https://openalex.org/W6798219303","https://openalex.org/W6799634771","https://openalex.org/W6800994093","https://openalex.org/W6802203484"],"related_works":["https://openalex.org/W3183948672","https://openalex.org/W3173606202","https://openalex.org/W3110381201","https://openalex.org/W2948807893","https://openalex.org/W2935909890","https://openalex.org/W2778153218","https://openalex.org/W2758277628","https://openalex.org/W1531601525","https://openalex.org/W2380179524","https://openalex.org/W4283365723"],"abstract_inverted_index":{"We":[0,101],"propose":[1,61],"a":[2,62,137,145,158],"modified":[3,104,142],"module":[4],"structure":[5],"of":[6,64,114,132,151],"FILM,":[7],"which":[8,92,162],"increases":[9],"its":[10],"performance":[11,35,113,131],"on":[12],"ALFRED":[13,108],"benchmark.":[14],"Despite":[15],"methods":[16],"like":[17],"imitation":[18],"learning":[19,22],"or":[20],"reinforcement":[21],"can":[23,76],"be":[24],"used,":[25],"we":[26,60,87],"will":[27],"show":[28],"it":[29],"is":[30,167],"possible":[31],"to":[32,46,55],"improve":[33],"the":[34,39,48,56,74,79,94,103,107,112,130,133,141,149],"by":[36,82],"simply":[37],"modifying":[38],"deterministic":[40],"policy":[41],"module.":[42],"our":[43],"approach":[44],"aims":[45],"use":[47],"semantic":[49,98],"segmented":[50],"visual":[51],"observation":[52],"when":[53],"navigating":[54],"target":[57,80],"location.":[58],"Additionally,":[59,140],"method":[63],"adaptive":[65],"decision":[66],"making":[67],"for":[68,78],"active":[69,72,165],"search.":[70],"Through":[71],"search,":[73],"agent":[75,95],"search":[77,166],"object":[81],"opening":[83],"closed":[84],"receptacles.":[85],"Also,":[86],"provide":[88],"some":[89,97],"minor":[90],"adjustments":[91],"helps":[93],"overcome":[96],"segmentation":[99],"errors.":[100],"evaluate":[102],"FILM":[105,143],"with":[106,116,122,136,157],"benchmark":[109],"and":[110,120],"achieved":[111],"25.37%":[115],"valid":[117,123],"seen":[118],"split":[119],"20.46%":[121],"unseen":[124],"split,":[125],"thus":[126],"succeeding":[127],"in":[128,148],"improving":[129],"original":[134],"architecture":[135],"small":[138],"margin.":[139],"showed":[144],"significant":[146],"improvement":[147],"result":[150],"task":[152],"type":[153],"\"Cool":[154],"&":[155],"Place\"":[156],"large":[159],"margin":[160],"(8.82%),":[161],"shows":[163],"that":[164],"effective.":[168]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-12-23T23:11:35.936235","created_date":"2025-10-10T00:00:00"}