{"id":"https://openalex.org/W4416034297","doi":"https://doi.org/10.18653/v1/2025.findings-emnlp.1125","title":"You Only Use Reactive Attention Slice When Retrieving From Long Context","display_name":"You Only Use Reactive Attention Slice When Retrieving From Long Context","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4416034297","doi":"https://doi.org/10.18653/v1/2025.findings-emnlp.1125"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2025.findings-emnlp.1125","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-emnlp.1125","pdf_url":"https://aclanthology.org/2025.findings-emnlp.1125.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":"Findings of the Association for Computational Linguistics: EMNLP 2025","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.findings-emnlp.1125.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026841800","display_name":"Yun Joon Soh","orcid":"https://orcid.org/0009-0004-5472-2006"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yun Joon Soh","raw_affiliation_strings":["University of California , San Diego"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California , San Diego","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100609556","display_name":"Hui Huang","orcid":"https://orcid.org/0000-0002-7600-2331"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hanxian Huang","raw_affiliation_strings":["University of California , San Diego"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California , San Diego","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106668475","display_name":"Yuandong Tian","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuandong Tian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5095044690","display_name":"Jishen Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jishen Zhao","raw_affiliation_strings":["University of California , San Diego"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California , San Diego","institution_ids":["https://openalex.org/I36258959"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.29789391,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"20665","last_page":"20686"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10918","display_name":"Memory Processes and Influences","score":0.03790000081062317,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10918","display_name":"Memory Processes and Influences","score":0.03790000081062317,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12607","display_name":"Personal Information Management and User Behavior","score":0.03269999846816063,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11094","display_name":"Face Recognition and Perception","score":0.024299999698996544,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6151000261306763},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.30250000953674316},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.29190000891685486},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.25040000677108765},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.23510000109672546}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6340000033378601},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6151000261306763},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5212000012397766},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.30250000953674316},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.29190000891685486},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2793000042438507},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.25040000677108765},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2362000048160553},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.23510000109672546},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.21379999816417694}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.findings-emnlp.1125","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-emnlp.1125","pdf_url":"https://aclanthology.org/2025.findings-emnlp.1125.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":"Findings of the Association for Computational Linguistics: EMNLP 2025","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.findings-emnlp.1125","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-emnlp.1125","pdf_url":"https://aclanthology.org/2025.findings-emnlp.1125.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":"Findings of the Association for Computational Linguistics: EMNLP 2025","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416034297.pdf","grobid_xml":"https://content.openalex.org/works/W4416034297.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Retrieval-Augmented":[0],"Generation":[1],"is":[2],"a":[3,48,58,71,76],"powerful":[4],"method":[5],"for":[6],"enhancing":[7],"language":[8],"models":[9],"(LMs),":[10],"but":[11],"existing":[12],"retrieval":[13,53],"techniques":[14],"are":[15,18,31],"limited.Embedding-based":[16],"methods":[17],"often":[19],"inaccurate":[20],"due":[21],"to":[22,34,70,80,105,112,115],"their":[23],"reliance":[24],"on":[25,85],"lexical":[26],"similarity,":[27],"while":[28],"neural":[29],"retrievers":[30],"computationally":[32],"expensive":[33],"train.To":[35],"overcome":[36],"these":[37],"issues,":[38],"we":[39],"introduce":[40],"You":[41],"Only":[42],"Use":[43],"Reactive":[44],"Attention":[45],"slice":[46],"(YOURA),":[47],"training-free":[49],"and":[50,92,107],"fine-tuning-free":[51],"attentionbased":[52],"technique.When":[54],"retrieving,":[55],"YOURA":[56],"uses":[57],"novel":[59],"reaction":[60],"score":[61],"heuristic,":[62],"which":[63],"quantifies":[64],"how":[65],"an":[66],"LM's":[67],"self-attention":[68],"\"reacts\"":[69],"user":[72],"query.We":[73],"also":[74],"propose":[75],"sentence":[77],"extraction":[78],"algorithm":[79],"efficiently":[81],"preprocess":[82],"the":[83,90],"context.Evaluations":[84],"three":[86],"open-source":[87],"LMs":[88],"using":[89],"LongBench":[91],"BABILong":[93],"datasets":[94],"show":[95],"YOURA's":[96],"effectiveness.Our":[97],"framework":[98],"improves":[99],"QA":[100],"task":[101],"accuracy":[102],"by":[103,110],"up":[104,111],"15%":[106],"inference":[108],"throughput":[109],"31%":[113],"compared":[114],"embedding-based":[116],"retrieval.":[117]},"counts_by_year":[],"updated_date":"2026-08-26T07:47:46.906454","created_date":"2025-11-08T00:00:00"}
