{"id":"https://openalex.org/W2889581211","doi":"https://doi.org/10.18653/v1/d18-1479","title":"Co-Stack Residual Affinity Networks with Multi-level Attention Refinement for Matching Text Sequences","display_name":"Co-Stack Residual Affinity Networks with Multi-level Attention Refinement for Matching Text Sequences","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2889581211","doi":"https://doi.org/10.18653/v1/d18-1479","mag":"2889581211"},"language":"en","primary_location":{"id":"doi:10.18653/v1/d18-1479","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d18-1479","pdf_url":"https://www.aclweb.org/anthology/D18-1479.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/D18-1479.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103069680","display_name":"Yi Tay","orcid":"https://orcid.org/0000-0001-6896-4496"},"institutions":[{"id":"https://openalex.org/I4210161496","display_name":"A*STAR Graduate Academy","ror":"https://ror.org/059yjzn93","country_code":"SG","type":"education","lineage":["https://openalex.org/I115228651","https://openalex.org/I4210161496"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yi Tay","raw_affiliation_strings":["Star Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Star Singapore","institution_ids":["https://openalex.org/I4210161496"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050386762","display_name":"Anh Tuan Luu","orcid":"https://orcid.org/0000-0002-1927-9895"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]},{"id":"https://openalex.org/I3005327000","display_name":"Institute for Infocomm Research","ror":"https://ror.org/053rfa017","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3005327000","https://openalex.org/I91275662"]},{"id":"https://openalex.org/I4210161496","display_name":"A*STAR Graduate Academy","ror":"https://ror.org/059yjzn93","country_code":"SG","type":"education","lineage":["https://openalex.org/I115228651","https://openalex.org/I4210161496"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Anh Tuan Luu","raw_affiliation_strings":["Nanyang Technological University, Singapore","Star Singapore","\u03c8 Institute for Infocomm Research, A"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"Star Singapore","institution_ids":["https://openalex.org/I4210161496"]},{"raw_affiliation_string":"\u03c8 Institute for Infocomm Research, A","institution_ids":["https://openalex.org/I3005327000"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077249934","display_name":"Siu Cheung Hui","orcid":"https://orcid.org/0000-0001-5397-4472"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]},{"id":"https://openalex.org/I3005327000","display_name":"Institute for Infocomm Research","ror":"https://ror.org/053rfa017","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3005327000","https://openalex.org/I91275662"]},{"id":"https://openalex.org/I4210161496","display_name":"A*STAR Graduate Academy","ror":"https://ror.org/059yjzn93","country_code":"SG","type":"education","lineage":["https://openalex.org/I115228651","https://openalex.org/I4210161496"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Siu Cheung Hui","raw_affiliation_strings":["Nanyang Technological University, Singapore","Star Singapore","\u03c8 Institute for Infocomm Research, A"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"Star Singapore","institution_ids":["https://openalex.org/I4210161496"]},{"raw_affiliation_string":"\u03c8 Institute for Infocomm Research, A","institution_ids":["https://openalex.org/I3005327000"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5050386762"],"corresponding_institution_ids":["https://openalex.org/I172675005","https://openalex.org/I3005327000","https://openalex.org/I4210161496"],"apc_list":null,"apc_paid":null,"fwci":2.49,"has_fulltext":true,"cited_by_count":37,"citation_normalized_percentile":{"value":0.92506272,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"4492","last_page":"4502"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":1.0,"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":1.0,"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":0.9998999834060669,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9958999752998352,"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/computer-science","display_name":"Computer science","score":0.8138473033905029},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5869175791740417},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5801813006401062},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5148895978927612},{"id":"https://openalex.org/keywords/intuition","display_name":"Intuition","score":0.4734717905521393},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.45317134261131287},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.18435990810394287}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8138473033905029},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5869175791740417},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5801813006401062},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5148895978927612},{"id":"https://openalex.org/C132010649","wikidata":"https://www.wikidata.org/wiki/Q189222","display_name":"Intuition","level":2,"score":0.4734717905521393},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.45317134261131287},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.18435990810394287},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/d18-1479","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d18-1479","pdf_url":"https://www.aclweb.org/anthology/D18-1479.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/d18-1479","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d18-1479","pdf_url":"https://www.aclweb.org/anthology/D18-1479.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2889581211.pdf","grobid_xml":"https://content.openalex.org/works/W2889581211.grobid-xml"},"referenced_works_count":65,"referenced_works":["https://openalex.org/W836999996","https://openalex.org/W1522301498","https://openalex.org/W1533861849","https://openalex.org/W1591825359","https://openalex.org/W1840435438","https://openalex.org/W1966443646","https://openalex.org/W2118463056","https://openalex.org/W2120735855","https://openalex.org/W2130942839","https://openalex.org/W2131876387","https://openalex.org/W2133564696","https://openalex.org/W2143612262","https://openalex.org/W2153702313","https://openalex.org/W2194775991","https://openalex.org/W2250539671","https://openalex.org/W2251427843","https://openalex.org/W2264105282","https://openalex.org/W2265289447","https://openalex.org/W2280395961","https://openalex.org/W2291880741","https://openalex.org/W2295739661","https://openalex.org/W2338325072","https://openalex.org/W2413794162","https://openalex.org/W2469060249","https://openalex.org/W2511929605","https://openalex.org/W2516930406","https://openalex.org/W2539338396","https://openalex.org/W2551396370","https://openalex.org/W2552027021","https://openalex.org/W2573379274","https://openalex.org/W2593833795","https://openalex.org/W2608787653","https://openalex.org/W2612867916","https://openalex.org/W2749909881","https://openalex.org/W2756386045","https://openalex.org/W2760753016","https://openalex.org/W2767501021","https://openalex.org/W2767857566","https://openalex.org/W2782363479","https://openalex.org/W2788496822","https://openalex.org/W2808281579","https://openalex.org/W2809057686","https://openalex.org/W2951528484","https://openalex.org/W2952113915","https://openalex.org/W2962685628","https://openalex.org/W2962739339","https://openalex.org/W2962854379","https://openalex.org/W2962958286","https://openalex.org/W2963053846","https://openalex.org/W2963077723","https://openalex.org/W2963446712","https://openalex.org/W2963508788","https://openalex.org/W2963615308","https://openalex.org/W2963719234","https://openalex.org/W2963756346","https://openalex.org/W2963871484","https://openalex.org/W2964012472","https://openalex.org/W2964026924","https://openalex.org/W2964084166","https://openalex.org/W2964121744","https://openalex.org/W2964308564","https://openalex.org/W3101747393","https://openalex.org/W4232449914","https://openalex.org/W4297567729","https://openalex.org/W4302343710"],"related_works":["https://openalex.org/W2364252372","https://openalex.org/W4234066492","https://openalex.org/W1998063895","https://openalex.org/W1967044713","https://openalex.org/W2560215812","https://openalex.org/W2949601986","https://openalex.org/W2133470120","https://openalex.org/W2788972299","https://openalex.org/W1994286895","https://openalex.org/W2747625183"],"abstract_inverted_index":{"Learning":[0],"a":[1,9,37,48,92,111],"matching":[2,153],"function":[3],"between":[4,116],"two":[5,79],"text":[6,151],"sequences":[7],"is":[8,47,123],"long":[10],"standing":[11],"problem":[12],"in":[13],"NLP":[14],"research.":[15],"This":[16,29],"task":[17],"enables":[18],"many":[19],"potential":[20],"applications":[21],"such":[22,68],"as":[23,69],"question":[24],"answering":[25],"and":[26,39,74],"paraphrase":[27],"identification.":[28],"paper":[30],"proposes":[31],"Co-Stack":[32],"Residual":[33],"Affinity":[34],"Networks":[35],"(CSRAN),":[36],"new":[38,93],"universal":[40],"neural":[41],"architecture":[42],"for":[43],"this":[44],"problem.":[45],"CSRAN":[46,77],"deep":[49],"architecture,":[50],"involving":[51],"stacked":[52,87,106,117],"(multi-layered)":[53],"recurrent":[54,118],"encoders.":[55],"Stacked/Deep":[56],"architectures":[57],"are":[58],"traditionally":[59],"difficult":[60],"to":[61,64,82],"train,":[62],"due":[63],"the":[65,86],"inherent":[66],"weaknesses":[67],"difficulty":[70],"with":[71],"feature":[72],"propagation":[73],"vanishing":[75],"gradients.":[76],"incorporates":[78],"novel":[80],"components":[81],"take":[83],"advantage":[84],"of":[85],"architecture.":[88],"Firstly,":[89],"it":[90,109],"introduces":[91],"bidirectional":[94],"alignment":[95],"mechanism":[96],"that":[97],"learns":[98],"affinity":[99],"weights":[100],"by":[101,125],"fusing":[102],"sequence":[103,152],"pairs":[104],"across":[105,128],"hierarchies.":[107],"Secondly,":[108],"leverages":[110],"multi-level":[112],"attention":[113],"refinement":[114],"component":[115],"layers.":[119],"The":[120],"key":[121],"intuition":[122],"that,":[124],"leveraging":[126],"information":[127],"all":[129],"network":[130],"hierarchies,":[131],"we":[132],"can":[133],"not":[134],"only":[135],"improve":[136,141],"gradient":[137],"flow":[138],"but":[139],"also":[140],"overall":[142],"performance.":[143],"We":[144],"conduct":[145],"extensive":[146],"experiments":[147],"on":[148,158],"six":[149],"well-studied":[150],"datasets,":[154],"achieving":[155],"state-of-the-art":[156],"performance":[157],"all.":[159]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":8}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}