{"id":"https://openalex.org/W7166847149","doi":"https://doi.org/10.18653/v1/2026.acl-long.1342","title":"LaCo: Layer-wise Compensation for Pruned Large Language Models","display_name":"LaCo: Layer-wise Compensation for Pruned Large Language Models","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7166847149","doi":"https://doi.org/10.18653/v1/2026.acl-long.1342"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2026.acl-long.1342","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.acl-long.1342","pdf_url":"https://aclanthology.org/2026.acl-long.1342.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.1342.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139790787","display_name":"Yingen Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]},{"id":"https://openalex.org/I24407930","display_name":"Hunan University of Science and Engineering","ror":"https://ror.org/04ymz0q33","country_code":"CN","type":"education","lineage":["https://openalex.org/I24407930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingen Liu","raw_affiliation_strings":["College of Computer Science and Electronic Engineering , Hunan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Electronic Engineering , Hunan University","institution_ids":["https://openalex.org/I16609230","https://openalex.org/I24407930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139830097","display_name":"Fan Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]},{"id":"https://openalex.org/I24407930","display_name":"Hunan University of Science and Engineering","ror":"https://ror.org/04ymz0q33","country_code":"CN","type":"education","lineage":["https://openalex.org/I24407930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Wu","raw_affiliation_strings":["College of Computer Science and Electronic Engineering , Hunan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Electronic Engineering , Hunan University","institution_ids":["https://openalex.org/I16609230","https://openalex.org/I24407930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139824302","display_name":"Panxuyan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Panxuyan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139717017","display_name":"Ruihui Li","orcid":null},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]},{"id":"https://openalex.org/I24407930","display_name":"Hunan University of Science and Engineering","ror":"https://ror.org/04ymz0q33","country_code":"CN","type":"education","lineage":["https://openalex.org/I24407930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruihui Li","raw_affiliation_strings":["College of Computer Science and Electronic Engineering , Hunan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Electronic Engineering , Hunan University","institution_ids":["https://openalex.org/I16609230","https://openalex.org/I24407930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139737717","display_name":"Zhuo Tang","orcid":null},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]},{"id":"https://openalex.org/I24407930","display_name":"Hunan University of Science and Engineering","ror":"https://ror.org/04ymz0q33","country_code":"CN","type":"education","lineage":["https://openalex.org/I24407930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuo Tang","raw_affiliation_strings":["College of Computer Science and Electronic Engineering , Hunan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Electronic Engineering , Hunan University","institution_ids":["https://openalex.org/I16609230","https://openalex.org/I24407930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5139845265","display_name":"Kenli Li","orcid":null},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]},{"id":"https://openalex.org/I24407930","display_name":"Hunan University of Science and Engineering","ror":"https://ror.org/04ymz0q33","country_code":"CN","type":"education","lineage":["https://openalex.org/I24407930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kenli Li","raw_affiliation_strings":["College of Computer Science and Electronic Engineering , Hunan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Electronic Engineering , Hunan University","institution_ids":["https://openalex.org/I16609230","https://openalex.org/I24407930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"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":0.83705713,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"29099","last_page":"29113"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.22439999878406525,"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":0.22439999878406525,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.09960000216960907,"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":0.09160000085830688,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/compensation","display_name":"Compensation (psychology)","score":0.28679999709129333},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.271699994802475},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.267300009727478},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.259799987077713},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.25690001249313354}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.57669997215271},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42329999804496765},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4117000102996826},{"id":"https://openalex.org/C2780023022","wikidata":"https://www.wikidata.org/wiki/Q1338171","display_name":"Compensation (psychology)","level":2,"score":0.28679999709129333},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2802000045776367},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.271699994802475},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.267300009727478},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.259799987077713},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.25690001249313354},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2515000104904175},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.25130000710487366},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.25}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2026.acl-long.1342","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.acl-long.1342","pdf_url":"https://aclanthology.org/2026.acl-long.1342.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.1342","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.acl-long.1342","pdf_url":"https://aclanthology.org/2026.acl-long.1342.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":[],"awards":[{"id":"https://openalex.org/G2744607400","display_name":null,"funder_award_id":"62225205","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4431121220","display_name":null,"funder_award_id":"62532005","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4480278818","display_name":null,"funder_award_id":"62472162","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/W7166847149.pdf","grobid_xml":"https://content.openalex.org/works/W7166847149.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Pruning":[0],"is":[1],"essential":[2],"for":[3],"the":[4,20,37,43,63,79,86,116],"efficient":[5],"deployment":[6],"of":[7,40,48,115],"Large":[8],"Language":[9],"Models":[10],"(LLMs);":[11],"however,":[12],"it":[13,107],"causes":[14],"severe":[15],"performance":[16],"degradation":[17],"due":[18],"to":[19,69,77,112,124],"structural":[21],"distortion":[22],"induced":[23],"by":[24],"sparsity.Existing":[25],"recovery":[26,64],"strategies,":[27],"such":[28],"as":[29],"LoRA,":[30],"predominantly":[31],"employ":[32],"global":[33,67],"finetuning,":[34],"often":[35],"overlooking":[36],"mechanistic":[38],"root":[39],"this":[41,52],"degradation:":[42],"layer-wise":[44],"accumulation":[45],"and":[46,104,118],"amplification":[47],"local":[49],"errors.To":[50],"address":[51],"limitation,":[53],"we":[54],"propose":[55],"LaCo":[56,83,96],"(Layerwise":[57],"Compensation),":[58],"a":[59,126,133],"framework":[60],"that":[61,95],"reorients":[62],"paradigm":[65],"from":[66],"adaptation":[68],"hierarchical":[70],"representation":[71],"alignment.By":[72],"sequentially":[73],"optimizing":[74],"each":[75],"layer":[76],"reconstruct":[78],"model's":[80],"hidden":[81],"states,":[82],"effectively":[84],"intercepts":[85],"error":[87],"propagation":[88],"chain":[89],"at":[90],"its":[91],"source.Extensive":[92],"experiments":[93],"demonstrate":[94],"surpasses":[97],"parameter-efficient":[98],"baselines":[99],"in":[100,137],"both":[101],"perplexity":[102],"reduction":[103],"zeroshot":[105],"reasoning.Notably,":[106],"reduces":[108],"recoverytime":[109],"memory":[110],"usage":[111],"approximately":[113],"1/7":[114],"baseline":[117],"requires":[119],"only":[120],"2,048":[121],"unlabeled":[122],"samples":[123],"match":[125],"LoRA":[127],"model":[128],"trained":[129],"on":[130],"50k":[131],"examples-achieving":[132],"\u223c":[134],"25\u00d7":[135],"improvement":[136],"data":[138],"efficiency.":[139]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-07-02T00:00:00"}
