{"id":"https://openalex.org/W3168641597","doi":"https://doi.org/10.1109/icme51207.2021.9428375","title":"Relative Position Representation over Interaction Space for Natural Language Inference","display_name":"Relative Position Representation over Interaction Space for Natural Language Inference","publication_year":2021,"publication_date":"2021-06-09","ids":{"openalex":"https://openalex.org/W3168641597","doi":"https://doi.org/10.1109/icme51207.2021.9428375","mag":"3168641597"},"language":"en","primary_location":{"id":"doi:10.1109/icme51207.2021.9428375","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme51207.2021.9428375","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5019517227","display_name":"Huiyan Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210111959","display_name":"Shanghai Advanced Research Institute","ror":"https://ror.org/02br7py06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210111959"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huiyan Wu","raw_affiliation_strings":["Chinese Academy of Sciences,Shanghai Advanced Research Institute","Shanghai Advanced Research Institute, Chinese Academy of Sciences","University of Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences,Shanghai Advanced Research Institute","institution_ids":["https://openalex.org/I4210111959"]},{"raw_affiliation_string":"Shanghai Advanced Research Institute, Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210111959"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054621636","display_name":"Jun Huang","orcid":"https://orcid.org/0000-0002-7706-7081"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210111959","display_name":"Shanghai Advanced Research Institute","ror":"https://ror.org/02br7py06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210111959"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Huang","raw_affiliation_strings":["Chinese Academy of Sciences,Shanghai Advanced Research Institute","Shanghai Advanced Research Institute, Chinese Academy of Sciences","University of Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences,Shanghai Advanced Research Institute","institution_ids":["https://openalex.org/I4210111959"]},{"raw_affiliation_string":"Shanghai Advanced Research Institute, Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210111959"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1465,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.35814604,"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":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9994999766349792,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9990000128746033,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9926000237464905,"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/sentence","display_name":"Sentence","score":0.6968716382980347},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.6244335174560547},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6074857711791992},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.573276937007904},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5445743203163147},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5270514488220215},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5258784294128418},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.48429813981056213},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.42567145824432373}],"concepts":[{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.6968716382980347},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.6244335174560547},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6074857711791992},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.573276937007904},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5445743203163147},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5270514488220215},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5258784294128418},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.48429813981056213},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.42567145824432373},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme51207.2021.9428375","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme51207.2021.9428375","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.8199999928474426,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1544827683","https://openalex.org/W1840435438","https://openalex.org/W2040103855","https://openalex.org/W2211192759","https://openalex.org/W2228826686","https://openalex.org/W2250539671","https://openalex.org/W2413794162","https://openalex.org/W2523467643","https://openalex.org/W2551396370","https://openalex.org/W2576562514","https://openalex.org/W2593833795","https://openalex.org/W2612867916","https://openalex.org/W2741989495","https://openalex.org/W2756386045","https://openalex.org/W2768523431","https://openalex.org/W2890223989","https://openalex.org/W2896457183","https://openalex.org/W2949615363","https://openalex.org/W2962958286","https://openalex.org/W2962998327","https://openalex.org/W2963241825","https://openalex.org/W2963446712","https://openalex.org/W2963542836","https://openalex.org/W2963925437","https://openalex.org/W2964338272","https://openalex.org/W4385245566","https://openalex.org/W6678150014","https://openalex.org/W6688494211","https://openalex.org/W6723749264","https://openalex.org/W6727238030","https://openalex.org/W6729654139","https://openalex.org/W6732426140","https://openalex.org/W6739901393","https://openalex.org/W6743583902","https://openalex.org/W6745771147","https://openalex.org/W6755207826"],"related_works":["https://openalex.org/W2375873920","https://openalex.org/W2146114872","https://openalex.org/W2392060890","https://openalex.org/W2055243143","https://openalex.org/W2392760275","https://openalex.org/W2083530853","https://openalex.org/W2982905616","https://openalex.org/W2009831055","https://openalex.org/W2393172683","https://openalex.org/W2368686738"],"abstract_inverted_index":{"In":[0,35,109],"natural":[1],"language":[2],"inference":[3],"(NLI),":[4],"attention":[5],"mechanism":[6],"has":[7],"achieved":[8],"great":[9],"success,":[10],"but":[11,69],"it":[12],"does":[13],"not":[14],"explicitly":[15],"model":[16,113,130],"order":[17],"information":[18,31,67],"between":[19,74,106],"sequential":[20],"elements.":[21],"Besides,":[22],"existing":[23],"models":[24],"for":[25],"NLI":[26],"tend":[27],"to":[28,92,101],"neglect":[29],"positional":[30],"of":[32,81,126],"inter-sentence":[33,107],"words.":[34,108],"this":[36,110],"paper,":[37],"we":[38],"propose":[39],"a":[40],"novel":[41],"relative":[42,62,65,103],"position":[43,80,104],"representation":[44],"over":[45,90],"interaction":[46],"space,":[47],"which":[48],"is":[49,99],"called":[50],"Distance":[51],"and":[52,64,128,137],"Direction":[53],"based":[54],"Relative":[55],"Position":[56],"Presentation":[57],"(D2RPR).":[58],"It":[59],"can":[60,114],"capture":[61,102],"distance":[63],"direction":[66],"simultaneously,":[68],"also":[70],"establish":[71],"potential":[72],"correlations":[73],"non-central":[75],"words":[76],"while":[77],"representing":[78],"the":[79,82,116,124],"central":[83],"word.":[84],"We":[85],"incorporate":[86],"D2RPR":[87,98,127],"into":[88],"self-attention":[89],"space":[91],"enhance":[93],"intra-sentence":[94],"contextual":[95],"connections.":[96],"Moreover,":[97],"used":[100],"relationships":[105],"way,":[111],"our":[112,129],"strengthen":[115],"semantic":[117],"connection":[118],"be-tween":[119],"sentences.":[120],"Experiment":[121],"results":[122],"show":[123],"effectiveness":[125],"achieves":[131],"competitive":[132],"performance":[133],"on":[134],"SNLI":[135],"dataset":[136],"Quora":[138],"dataset.":[139]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
