{"id":"https://openalex.org/W4416035428","doi":"https://doi.org/10.18653/v1/2025.emnlp-main.1612","title":"3R: Enhancing Sentence Representation Learning via Redundant Representation Reduction","display_name":"3R: Enhancing Sentence Representation Learning via Redundant Representation Reduction","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4416035428","doi":"https://doi.org/10.18653/v1/2025.emnlp-main.1612"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2025.emnlp-main.1612","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.emnlp-main.1612","pdf_url":"https://aclanthology.org/2025.emnlp-main.1612.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 2025 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://aclanthology.org/2025.emnlp-main.1612.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5040643252","display_name":"Longxuan Ma","orcid":"https://orcid.org/0000-0003-1431-8485"},"institutions":[{"id":"https://openalex.org/I4210116091","display_name":"Department of Physics, Mathematics and Informatics","ror":"https://ror.org/023sm4k53","country_code":"BY","type":"facility","lineage":["https://openalex.org/I151823869","https://openalex.org/I4210116091"]}],"countries":["BY"],"is_corresponding":false,"raw_author_name":"Longxuan Ma","raw_affiliation_strings":["university of science and technology Faculty of Information Engineering and Automation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"university of science and technology Faculty of Information Engineering and Automation","institution_ids":["https://openalex.org/I4210116091"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011680564","display_name":"Xiao Wu","orcid":"https://orcid.org/0000-0002-8322-8558"},"institutions":[{"id":"https://openalex.org/I4210116091","display_name":"Department of Physics, Mathematics and Informatics","ror":"https://ror.org/023sm4k53","country_code":"BY","type":"facility","lineage":["https://openalex.org/I151823869","https://openalex.org/I4210116091"]}],"countries":["BY"],"is_corresponding":false,"raw_author_name":"Xiao Wu","raw_affiliation_strings":["university of science and technology Faculty of Information Engineering and Automation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"university of science and technology Faculty of Information Engineering and Automation","institution_ids":["https://openalex.org/I4210116091"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102000309","display_name":"Yuxin Huang","orcid":"https://orcid.org/0000-0003-4212-0644"},"institutions":[{"id":"https://openalex.org/I4210116091","display_name":"Department of Physics, Mathematics and Informatics","ror":"https://ror.org/023sm4k53","country_code":"BY","type":"facility","lineage":["https://openalex.org/I151823869","https://openalex.org/I4210116091"]}],"countries":["BY"],"is_corresponding":false,"raw_author_name":"Yuxin Huang","raw_affiliation_strings":["university of science and technology Faculty of Information Engineering and Automation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"university of science and technology Faculty of Information Engineering and Automation","institution_ids":["https://openalex.org/I4210116091"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017471172","display_name":"Shengxiang Gao","orcid":"https://orcid.org/0000-0002-2980-8420"},"institutions":[{"id":"https://openalex.org/I4210116091","display_name":"Department of Physics, Mathematics and Informatics","ror":"https://ror.org/023sm4k53","country_code":"BY","type":"facility","lineage":["https://openalex.org/I151823869","https://openalex.org/I4210116091"]}],"countries":["BY"],"is_corresponding":false,"raw_author_name":"Shengxiang Gao","raw_affiliation_strings":["university of science and technology Faculty of Information Engineering and Automation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"university of science and technology Faculty of Information Engineering and Automation","institution_ids":["https://openalex.org/I4210116091"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100619287","display_name":"Zhengtao Yu","orcid":"https://orcid.org/0000-0002-4012-461X"},"institutions":[{"id":"https://openalex.org/I4210116091","display_name":"Department of Physics, Mathematics and Informatics","ror":"https://ror.org/023sm4k53","country_code":"BY","type":"facility","lineage":["https://openalex.org/I151823869","https://openalex.org/I4210116091"]}],"countries":["BY"],"is_corresponding":false,"raw_author_name":"Zhengtao Yu","raw_affiliation_strings":["university of science and technology Faculty of Information Engineering and Automation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"university of science and technology Faculty of Information Engineering and Automation","institution_ids":["https://openalex.org/I4210116091"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210116091"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.30127216,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"31618","last_page":"31631"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.21480000019073486,"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":0.21480000019073486,"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":0.1492999941110611,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.056299999356269836,"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/representation","display_name":"Representation (politics)","score":0.58160001039505},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.4489000141620636},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.37119999527931213},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.3402000069618225},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.32190001010894775}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6233000159263611},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6129000186920166},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.58160001039505},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.4489000141620636},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.37119999527931213},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.37070000171661377},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3402000069618225},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.32190001010894775},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.2935999929904938},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.28529998660087585},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.257999986410141}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.emnlp-main.1612","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.emnlp-main.1612","pdf_url":"https://aclanthology.org/2025.emnlp-main.1612.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 2025 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.emnlp-main.1612","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.emnlp-main.1612","pdf_url":"https://aclanthology.org/2025.emnlp-main.1612.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 2025 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3894850591","display_name":null,"funder_award_id":"62266027","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4479882814","display_name":null,"funder_award_id":"U21B2027","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G597367334","display_name":null,"funder_award_id":"6226\u20136028","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":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416035428.pdf","grobid_xml":"https://content.openalex.org/works/W4416035428.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Sentence":[0],"representation":[1],"learning":[2,27],"(SRL)":[3],"aims":[4],"to":[5,11,72,104],"learn":[6],"sentence":[7,35,48,65,113],"embeddings":[8,46,53],"that":[9,89],"conform":[10],"the":[12,32,38,62,74,101,123,128,134,140],"semantic":[13,39,118],"information":[14,95],"of":[15,34,41,64,127,133],"sentences.In":[16],"recent":[17],"years,":[18],"fine-tuning":[19],"methods":[20],"based":[21],"on":[22,80,107],"pre-trained":[23],"models":[24],"and":[25,47,92,110,125,139],"contrastive":[26],"frameworks":[28],"have":[29],"significantly":[30],"advanced":[31],"quality":[33],"representations.However,":[36],"within":[37],"space":[40],"SRL":[42,102],"models,":[43],"both":[44],"word":[45,52],"representations":[49],"derived":[50],"from":[51],"exhibit":[54],"substantial":[55],"redundant":[56,82,94],"information,":[57],"which":[58],"can":[59],"adversely":[60],"affect":[61],"precision":[63],"representations.Existing":[66],"approaches":[67],"predominantly":[68],"optimize":[69],"training":[70,100],"strategies":[71],"alleviate":[73],"redundancy":[75],"problem,":[76],"lacking":[77],"fine-grained":[78],"guidance":[79],"reducing":[81],"representations.This":[83],"paper":[84],"proposes":[85],"a":[86,97],"novel":[87],"approach":[88],"dynamically":[90],"identifies":[91],"reduces":[93],"in":[96],"dimensional":[98],"perspective,":[99],"model":[103],"redistribute":[105],"semantics":[106],"different":[108],"dimensions,":[109],"entailing":[111],"better":[112],"representations.Extensive":[114],"experiments":[115],"across":[116],"seven":[117],"text":[119],"similarity":[120],"benchmarks":[121],"demonstrate":[122],"effectiveness":[124],"generality":[126],"proposed":[129],"method.A":[130],"comprehensive":[131],"analysis":[132],"experimental":[135],"results":[136],"is":[137],"conducted":[138],"code/data":[141],"will":[142],"be":[143],"released.":[144]},"counts_by_year":[],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-11-08T00:00:00"}