{"id":"https://openalex.org/W4417529994","doi":"https://doi.org/10.48550/arxiv.2512.16282","title":"CALM: A CKA-Guided Adaptive Layer-Wise Modularization Framework for LLM Quantization","display_name":"CALM: A CKA-Guided Adaptive Layer-Wise Modularization Framework for LLM Quantization","publication_year":2025,"publication_date":"2025-12-18","ids":{"openalex":"https://openalex.org/W4417529994","doi":"https://doi.org/10.48550/arxiv.2512.16282"},"language":null,"primary_location":{"id":"pmh:oai:arXiv.org:2512.16282","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.16282","pdf_url":"https://arxiv.org/pdf/2512.16282","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2512.16282","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5073912741","display_name":"Jinhao Zhang","orcid":"https://orcid.org/0000-0002-3661-1845"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zhang, Jinhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001666028","display_name":"Yunquan Zhang","orcid":"https://orcid.org/0000-0002-2618-5088"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yunquan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086846872","display_name":"Daning Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Daning","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"JunSun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"JunSun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Yan, Zicheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yan, Zicheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5073912741"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"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":0.13289999961853027,"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":0.13289999961853027,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.12380000203847885,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.10400000214576721,"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/quantization","display_name":"Quantization (signal processing)","score":0.7979999780654907},{"id":"https://openalex.org/keywords/vector-quantization","display_name":"Vector quantization","score":0.4099999964237213},{"id":"https://openalex.org/keywords/linde\u2013buzo\u2013gray-algorithm","display_name":"Linde\u2013Buzo\u2013Gray algorithm","score":0.35409998893737793},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.33160001039505005},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.3212999999523163},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.32120001316070557}],"concepts":[{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.7979999780654907},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.633400022983551},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.47749999165534973},{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.4099999964237213},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3628000020980835},{"id":"https://openalex.org/C93372532","wikidata":"https://www.wikidata.org/wiki/Q6552455","display_name":"Linde\u2013Buzo\u2013Gray algorithm","level":3,"score":0.35409998893737793},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.33160001039505005},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.32190001010894775},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.3212999999523163},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.32120001316070557},{"id":"https://openalex.org/C100279451","wikidata":"https://www.wikidata.org/wiki/Q372193","display_name":"Perplexity","level":3,"score":0.3156000077724457},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30320000648498535},{"id":"https://openalex.org/C88482812","wikidata":"https://www.wikidata.org/wiki/Q6453666","display_name":"Modular programming","level":2,"score":0.2874999940395355},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2759000062942505},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.26570001244544983},{"id":"https://openalex.org/C92757383","wikidata":"https://www.wikidata.org/wiki/Q382497","display_name":"Affine transformation","level":2,"score":0.2542000114917755}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2512.16282","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.16282","pdf_url":"https://arxiv.org/pdf/2512.16282","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2512.16282","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2512.16282","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2512.16282","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.16282","pdf_url":"https://arxiv.org/pdf/2512.16282","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Current":[0],"mainstream":[1,104],"post-training":[2],"quantization":[3,13,71,97],"methods":[4,102],"for":[5,43],"large":[6],"language":[7],"models":[8],"typically":[9],"apply":[10],"a":[11,64,84],"uniform":[12,96],"strategy":[14,72],"across":[15,103],"all":[16],"network":[17],"layers,":[18],"overlooking":[19],"the":[20,69],"substantial":[21],"differences":[22],"in":[23],"algorithmic":[24,44],"suitability":[25],"among":[26],"layers.":[27],"To":[28],"address":[29],"this":[30],"limitation,":[31],"we":[32],"propose":[33],"CALM":[34,47],"(A":[35],"CKA-guided":[36],"Adaptive":[37],"Layer-wise":[38],"Modularization)a":[39],"fine-tuning-free,":[40],"plug-and-play":[41],"framework":[42],"heterogeneous":[45],"quantization.":[46],"independently":[48],"evaluates":[49],"multiple":[50],"PTQ":[51],"algorithms":[52],"on":[53],"each":[54],"layer":[55],"and":[56,99,107,113],"employs":[57],"Linear":[58],"Centered":[59],"Kernel":[60],"Alignment":[61],"(CKA)":[62],"as":[63],"metric":[65],"to":[66,82],"automatically":[67],"select":[68],"optimal":[70],"per":[73],"layer.":[74],"The":[75],"individually":[76],"optimized":[77],"strategies":[78],"are":[79],"then":[80],"integrated":[81],"construct":[83],"hybrid":[85],"quantized":[86],"model.":[87],"Experiments":[88],"demonstrate":[89],"that":[90],"our":[91],"approach":[92],"consistently":[93],"outperforms":[94],"both":[95],"baselines":[98],"state-of-the-art":[100],"mixed-precision":[101],"LLMsincluding":[105],"LLaMA":[106],"Qwenin":[108],"terms":[109],"of":[110],"perplexity":[111],"(PPL)":[112],"downstream":[114],"task":[115],"performance.":[116]},"counts_by_year":[],"updated_date":"2026-06-02T09:04:35.204637","created_date":"2025-12-21T00:00:00"}
