{"id":"https://openalex.org/W7166847147","doi":"https://doi.org/10.18653/v1/2026.findings-acl.1058","title":"Adaptive Zooming via Relevance-Informed Positional Resource Allocation for Training-free LLM Context Extension","display_name":"Adaptive Zooming via Relevance-Informed Positional Resource Allocation for Training-free LLM Context Extension","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7166847147","doi":"https://doi.org/10.18653/v1/2026.findings-acl.1058"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2026.findings-acl.1058","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.1058","pdf_url":"https://aclanthology.org/2026.findings-acl.1058.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.1058.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139816924","display_name":"Hongbo Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hongbo Zhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139734884","display_name":"Huibin Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huibin Wang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139760451","display_name":"Bin Tang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bin Tang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139725348","display_name":"Xianming Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xianming Hu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139729288","display_name":"Yihong Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yihong Huang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139801685","display_name":"Yijun Shen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yijun Shen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113377586","display_name":"Nuoyi Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nuoyi Chen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139817613","display_name":"Ping Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ping Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139787780","display_name":"Kai Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kai Zhang","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":0.83703054,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"21067","last_page":"21083"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.25529998540878296,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.25529998540878296,"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":0.09229999780654907,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.07609999924898148,"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/context","display_name":"Context (archaeology)","score":0.6330000162124634},{"id":"https://openalex.org/keywords/extension","display_name":"Extension (predicate logic)","score":0.6103000044822693},{"id":"https://openalex.org/keywords/zoom","display_name":"Zoom","score":0.4970000088214874},{"id":"https://openalex.org/keywords/resource-allocation","display_name":"Resource allocation","score":0.4932999908924103},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.45260000228881836}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6693999767303467},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6330000162124634},{"id":"https://openalex.org/C2778029271","wikidata":"https://www.wikidata.org/wiki/Q5421931","display_name":"Extension (predicate logic)","level":2,"score":0.6103000044822693},{"id":"https://openalex.org/C124913957","wikidata":"https://www.wikidata.org/wiki/Q1232548","display_name":"Zoom","level":3,"score":0.4970000088214874},{"id":"https://openalex.org/C29202148","wikidata":"https://www.wikidata.org/wiki/Q287260","display_name":"Resource allocation","level":2,"score":0.4932999908924103},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.45260000228881836},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.38339999318122864},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33149999380111694},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2743000090122223},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.266400009393692},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2506999969482422}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2026.findings-acl.1058","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.1058","pdf_url":"https://aclanthology.org/2026.findings-acl.1058.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.1058","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.1058","pdf_url":"https://aclanthology.org/2026.findings-acl.1058.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/G6304150607","display_name":null,"funder_award_id":"62276099","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":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7166847147.pdf","grobid_xml":"https://content.openalex.org/works/W7166847147.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"Language":[1],"Models":[2],"exhibit":[3],"degraded":[4],"performance":[5],"when":[6],"extrapolating":[7],"beyond":[8],"training":[9],"context":[10,83,129],"lengths.Existing":[11],"training-free":[12,170],"methods":[13],"like":[14],"positional":[15,53,63,74,96,112,116,178],"reuse":[16],"or":[17],"interpolation":[18],"can":[19],"alleviate":[20],"this":[21],"issue":[22],"in":[23,70,80],"an":[24,51,134],"efficient":[25],"manner.However,":[26],"these":[27],"strategies":[28],"are":[29,102],"semantics-agnostic":[30],"by":[31],"only":[32],"considering":[33],"relative":[34],"token":[35],"distances,":[36],"which":[37,71],"could":[38],"indiscriminately":[39],"blur":[40],"semantically":[41],"relevant":[42,92],"and":[43,110,123,131,150],"irrelevant":[44,99],"tokens":[45,79,93,100],"alike.To":[46],"address":[47],"this,":[48,105],"we":[49],"introduce":[50],"adaptive":[52],"zooming":[54,113],"method":[55],"called":[56],"Relevance-Informed":[57],"Positional":[58],"Resource":[59],"Allocation":[60],"(RiPRA).RiPRA":[61],"formulates":[62],"encoding":[64,179],"as":[65],"a":[66,72,81,108,142,154],"constrained":[67],"resource":[68],"allocation,":[69],"fixed":[73],"budget":[75],"is":[76,118,137],"distributed":[77],"across":[78,121],"longer":[82],"based":[84],"on":[85],"their":[86],"semantic":[87],"relevance":[88],"to":[89,139,147,158],"the":[90,115,174],"query:":[91],"get":[94],"higher":[95],"resolution,":[97],"while":[98],"(positions)":[101],"compressed.By":[103],"doing":[104],"RiPRA":[106,166],"enables":[107],"dynamic":[109],"nonparametric":[111],"where":[114],"resolution":[117],"adaptively":[119],"modulated":[120],"queries":[122],"network":[124],"layers,":[125],"effectively":[126],"improving":[127],"long-range":[128],"modeling":[130],"retrieval":[132],"capacity.Besides,":[133],"isotonic":[135],"smoothing":[136],"used":[138],"further":[140,159],"enforce":[141],"global":[143],"linear":[144],"ordering":[145],"relationship":[146],"preserve":[148],"stability":[149],"generalization,":[151],"together":[152],"with":[153],"chunk-based":[155],"hierarchical":[156],"approximation":[157],"reduce":[160],"inference":[161],"overhead.Extensive":[162],"experiments":[163],"demonstrate":[164],"that":[165],"consistently":[167],"outperforms":[168],"existing":[169],"extrapolation":[171],"methods,":[172],"showing":[173],"value":[175],"of":[176],"relevance-conditioned":[177],"for":[180],"long-context":[181],"generalization.":[182]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-07-02T00:00:00"}