{"id":"https://openalex.org/W7166869645","doi":"https://doi.org/10.18653/v1/2026.acl-long.183","title":"IMPACT: Importance-Aware Activation Space Reconstruction","display_name":"IMPACT: Importance-Aware Activation Space Reconstruction","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7166869645","doi":"https://doi.org/10.18653/v1/2026.acl-long.183"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2026.acl-long.183","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.acl-long.183","pdf_url":"https://aclanthology.org/2026.acl-long.183.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 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2026.acl-long.183.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139743720","display_name":"Md Mokarram Chowdhury","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Md Mokarram Chowdhury","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120274697","display_name":"Daniel Agyei Asante","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Daniel Agyei Asante","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139781098","display_name":"Ernie Chang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ernie Chang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139744315","display_name":"Yang Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang Li","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":0.85833599,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3975","last_page":"3992"},"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":0.046300001442432404,"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":0.046300001442432404,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.04430000111460686,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.026599999517202377,"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/space","display_name":"Space (punctuation)","score":0.3652999997138977},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.26829999685287476},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.2517000138759613}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.37450000643730164},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.3652999997138977},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.337799996137619},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3100999891757965},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27309998869895935},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2727999985218048},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.26829999685287476},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2563000023365021},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.2517000138759613},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.2513999938964844}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2026.acl-long.183","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.acl-long.183","pdf_url":"https://aclanthology.org/2026.acl-long.183.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 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2026.acl-long.183","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.acl-long.183","pdf_url":"https://aclanthology.org/2026.acl-long.183.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 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.4702872633934021,"id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G2935245558","display_name":"MRI: Acquisition of a HPC System: Computing for Sustainability","funder_award_id":"1726447","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G446664095","display_name":null,"funder_award_id":"2018594","funder_id":"https://openalex.org/F4320311090","funder_display_name":"Iowa State University"},{"id":"https://openalex.org/G4724562758","display_name":"MRI: Acquisition of a Shared High-Performance Computing System for  Cyber-Enabled System Design","funder_award_id":"2018594","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8697713425","display_name":null,"funder_award_id":"1726447","funder_id":"https://openalex.org/F4320311090","funder_display_name":"Iowa State University"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320311090","display_name":"Iowa State University","ror":"https://ror.org/04rswrd78"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7166869645.pdf","grobid_xml":"https://content.openalex.org/works/W7166869645.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2,139],"(LLMs)":[3],"achieve":[4],"strong":[5],"performance":[6],"across":[7,137],"diverse":[8],"domains":[9],"but":[10],"remain":[11],"difficult":[12],"to":[13,19,74,83,96,147,157],"deploy":[14],"in":[15,45],"resource-constrained":[16],"environments":[17],"due":[18],"their":[20],"size.Low-rank":[21],"compression":[22,95,103,131],"is":[23,66],"a":[24,51,116],"common":[25],"remedy,":[26],"typically":[27],"minimizing":[28],"weight":[29],"reconstruction":[30,61,91,120],"error":[31],"under":[32],"the":[33],"assumption":[34,40],"that":[35,58,93,108,143],"weights":[36],"are":[37],"low-rank.However,":[38],"this":[39],"often":[41],"does":[42],"not":[43,67],"hold":[44],"LLMs.In":[46],"contrast,":[47],"LLM":[48],"activations":[49],"exhibit":[50],"more":[52],"pronounced":[53],"low-rank":[54],"structure,":[55],"motivating":[56],"approaches":[57],"minimize":[59],"activation":[60,70,90,110,126],"error.This":[62],"shift":[63],"alone,":[64],"however,":[65],"sufficient:":[68],"different":[69],"dimensions":[71],"contribute":[72],"unequally":[73],"model":[75,100,150],"performance,":[76],"and":[77,140],"treating":[78],"them":[79],"uniformly":[80],"can":[81],"lead":[82],"accuracy":[84,135,155],"loss.We":[85],"introduce":[86],"IMPACT,":[87],"an":[88,105,124],"importance-aware":[89],"framework":[92],"links":[94],"its":[97],"effect":[98],"on":[99],"performance.IMPACT":[101],"formulates":[102],"as":[104],"optimization":[106],"problem":[107],"integrates":[109],"structure":[111],"with":[112],"gradient-based":[113],"importance,":[114],"deriving":[115],"closed-form":[117],"solution":[118],"where":[119],"bases":[121],"arise":[122],"from":[123],"importance-weighted":[125],"covariance":[127],"matrix.This":[128],"yields":[129],"lowrank":[130],"explicitly":[132],"optimized":[133],"for":[134],"preservation.Experiments":[136],"multiple":[138],"tasks":[141],"demonstrate":[142],"IMPACT":[144],"achieves":[145],"up":[146],"55.4%":[148],"greater":[149],"size":[151],"reduction":[152],"while":[153],"maintaining":[154],"comparable":[156],"or":[158],"better":[159],"than":[160],"state-of-the-art":[161],"baselines.":[162]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-07-02T00:00:00"}
