{"id":"https://openalex.org/W7166860017","doi":"https://doi.org/10.18653/v1/2026.findings-acl.666","title":"LLMs Meet Isolation Kernel: Lightweight, Learning-free Binary Embeddings for Fast Retrieval","display_name":"LLMs Meet Isolation Kernel: Lightweight, Learning-free Binary Embeddings for Fast Retrieval","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7166860017","doi":"https://doi.org/10.18653/v1/2026.findings-acl.666"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2026.findings-acl.666","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.666","pdf_url":"https://aclanthology.org/2026.findings-acl.666.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: ACL 2026","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2026.findings-acl.666.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139795230","display_name":"Zhibo Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhibo Zhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139784402","display_name":"Yang Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang Xu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139798869","display_name":"Kai Ming Ting","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kai Ming Ting","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139815684","display_name":"Cam-Tu Nguyen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cam-Tu Nguyen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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":0.84849452,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"13601","last_page":"13623"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.20100000500679016,"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":0.20100000500679016,"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":0.09430000185966492,"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":0.09040000289678574,"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/binary-number","display_name":"Binary number","score":0.5493999719619751},{"id":"https://openalex.org/keywords/isolation","display_name":"Isolation (microbiology)","score":0.42890000343322754},{"id":"https://openalex.org/keywords/binary-data","display_name":"Binary data","score":0.39469999074935913},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3005000054836273},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.30000001192092896}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5896999835968018},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.5493999719619751},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5249999761581421},{"id":"https://openalex.org/C2775941552","wikidata":"https://www.wikidata.org/wiki/Q25212305","display_name":"Isolation (microbiology)","level":2,"score":0.42890000343322754},{"id":"https://openalex.org/C2779190172","wikidata":"https://www.wikidata.org/wiki/Q4913888","display_name":"Binary data","level":3,"score":0.39469999074935913},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3005000054836273},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.30000001192092896},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2955999970436096},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.27559998631477356},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.25999999046325684},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.25850000977516174}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2026.findings-acl.666","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.666","pdf_url":"https://aclanthology.org/2026.findings-acl.666.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: ACL 2026","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2026.findings-acl.666","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.666","pdf_url":"https://aclanthology.org/2026.findings-acl.666.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: ACL 2026","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6078157221","display_name":null,"funder_award_id":"W2531050","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7202014333","display_name":null,"funder_award_id":"92470116","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7957610226","display_name":null,"funder_award_id":"JYB2025XDXM118","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"},{"id":"https://openalex.org/F4320321106","display_name":"Ministry of Education of the People's Republic of China","ror":"https://ror.org/01mv9t934"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7166860017.pdf","grobid_xml":"https://content.openalex.org/works/W7166860017.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2],"(LLMs)":[3],"have":[4],"recently":[5],"enabled":[6],"remarkable":[7],"progress":[8],"in":[9,159,169],"text":[10,93],"representation.However,":[11],"their":[12],"embeddings":[13],"are":[14],"typically":[15],"high-dimensional,":[16],"leading":[17],"to":[18,40,101,140,165],"substantial":[19],"storage":[20],"and":[21,32,73,84,105,148,162],"retrieval":[22,47,89,94,104,146],"overhead.Although":[23],"recent":[24],"approaches":[25],"such":[26],"as":[27],"Matryoshka":[28],"Representation":[29,35],"Learning":[30],"(MRL)":[31],"Contrastive":[33],"Sparse":[34],"(CSR)":[36],"alleviate":[37],"these":[38],"issues":[39],"some":[41],"extent,":[42],"they":[43],"still":[44],"suffer":[45],"from":[46],"accuracy":[48,161],"degradation.This":[49],"paper":[50],"proposes":[51],"Isolation":[52,70],"Kernel":[53,71],"Embedding":[54],"or":[55],"IKE,":[56],"a":[57,66,80],"learning-free":[58],"method":[59],"that":[60,97,121,134],"transforms":[61],"an":[62],"LLM":[63,113],"embedding":[64,68],"into":[65],"binary":[67,76,132],"using":[69],"(IK).Lightweight":[72],"based":[74],"on":[75,91],"encoding,":[77],"IKE":[78,98,122,142],"offers":[79,99],"low":[81],"memory":[82,108],"footprint":[83],"fast":[85],"bitwise":[86],"computation,":[87],"lowering":[88],"latency.Experiments":[90],"multiple":[92],"datasets":[95],"demonstrate":[96],"up":[100],"16.7\u00d7":[102],"faster":[103],"16\u00d7":[106],"lower":[107],"usage":[109],"than":[110],"the":[111,170],"original":[112],"embeddings,":[114],"while":[115],"maintaining":[116],"comparable":[117],"accuracy.Theoretically,":[118],"we":[119],"show":[120],"works":[123,151],"because":[124],"it":[125],"satisfies":[126],"four":[127],"essential":[128],"criteria":[129],"for":[130],"effective":[131],"hashing":[133],"other":[135],"methods":[136],"do":[137],"not":[138],"possess.Compared":[139],"CSR,":[141],"consistently":[143],"achieves":[144],"better":[145],"efficiency":[147],"effectiveness.IKE":[149],"also":[150],"effectively":[152],"with":[153],"graph-based":[154],"indexing,":[155],"demonstrating":[156],"its":[157],"superiority":[158],"balancing":[160],"latency":[163],"compared":[164],"alternative":[166],"compression":[167],"techniques":[168],"approximate":[171],"nearest":[172],"neighbor":[173],"(ANN)":[174],"search":[175],"setting.":[176]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-07-02T00:00:00"}
