{"id":"https://openalex.org/W7162556827","doi":"https://doi.org/10.48550/arxiv.2605.26175","title":"InfoQuant: Shaping Activation Distributions for Low-Bit LLM Quantization","display_name":"InfoQuant: Shaping Activation Distributions for Low-Bit LLM Quantization","publication_year":2026,"publication_date":"2026-05-25","ids":{"openalex":"https://openalex.org/W7162556827","doi":"https://doi.org/10.48550/arxiv.2605.26175"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.26175","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.26175","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":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.26175","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137174964","display_name":"Ke Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Ke","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101445699","display_name":"Dong An","orcid":"https://orcid.org/0000-0002-8526-2290"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"An, Dong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137188345","display_name":"Xiaoling Zang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zang, Xiaoling","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137124293","display_name":"Can Ye","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ye, Can","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137114449","display_name":"Liang Xie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Liang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055301514","display_name":"Qibo Qiu","orcid":"https://orcid.org/0000-0002-2848-6079"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qiu, Qibo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137179409","display_name":"Chen Shen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shen, Chen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137116737","display_name":"Xiaofei He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Xiaofei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137151513","display_name":"Wenxiao Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Wenxiao","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":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/T10036","display_name":"Advanced Neural Network Applications","score":0.5382999777793884,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.5382999777793884,"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":0.038100000470876694,"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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.0364999994635582,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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":0.7964000105857849},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5016000270843506},{"id":"https://openalex.org/keywords/vector-quantization","display_name":"Vector quantization","score":0.37630000710487366},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.3215999901294708},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.30489999055862427},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.28540000319480896}],"concepts":[{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.7964000105857849},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5891000032424927},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5321000218391418},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5016000270843506},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.41130000352859497},{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.37630000710487366},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.3215999901294708},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.30489999055862427},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.28540000319480896},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.26919999718666077},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.2678000032901764},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.2603999972343445},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.2574000060558319}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.26175","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.26175","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.26175","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.26175","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":false,"raw_source_name":null,"raw_type":"Preprint"},"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":{"Low-bit":[0],"activation":[1,54,94],"quantization":[2,38,73,77,102],"remains":[3,79],"a":[4,32,62,86,117,134],"major":[5],"bottleneck":[6],"in":[7],"efficient":[8],"large":[9,72],"language":[10],"model":[11],"(LLM)":[12],"deployment.":[13],"The":[14],"difficulty":[15],"is":[16,56,205],"not":[17],"only":[18],"that":[19,24,111,125,137],"activations":[20,64,113,146],"contain":[21],"outliers,":[22],"but":[23],"their":[25],"distributions":[26],"are":[27],"often":[28],"poorly":[29],"matched":[30],"to":[31,59,144,157],"low-bit":[33],"uniform":[34],"quantizer.":[35],"Existing":[36],"post-training":[37],"(PTQ)":[39],"methods":[40],"suppress":[41],"peaks,":[42],"balance":[43],"channels,":[44],"or":[45,81],"minimize":[46],"reconstruction":[47],"error,":[48],"yet":[49],"they":[50],"rarely":[51],"specify":[52],"what":[53],"distribution":[55,98],"actually":[57],"easy":[58],"discretize.":[60],"As":[61],"result,":[63],"may":[65],"appear":[66],"numerically":[67],"smoother":[68],"while":[69],"still":[70],"incurring":[71],"error":[74,103],"because":[75],"the":[76,90,159,190,198,202],"range":[78,120],"wide":[80],"most":[82],"values":[83],"collapse":[84],"into":[85,147],"few":[87],"levels":[88],"near":[89],"mean.":[91],"We":[92,151],"recast":[93],"transformation":[95],"as":[96],"quantizer-facing":[97],"design":[99],"and":[100,121,174,188],"analyze":[101],"from":[104],"an":[105],"information-theoretic":[106],"perspective.":[107],"Our":[108],"analysis":[109],"shows":[110],"quantization-friendly":[112,149],"should":[114],"jointly":[115],"have":[116],"smaller":[118],"numerical":[119],"sufficient":[122],"dispersion":[123],"within":[124],"range.":[126],"Guided":[127],"by":[128,195],"this":[129],"analysis,":[130],"we":[131],"propose":[132],"InfoQuant,":[133],"train-free":[135],"method":[136],"employs":[138],"Peak":[139],"Suppression":[140],"Orthogonal":[141],"Transformation":[142],"(PSOT)":[143],"shape":[145],"more":[148],"distributions.":[150],"further":[152],"introduce":[153],"adaptive":[154],"outlier-token":[155],"selection":[156],"improve":[158],"robustness":[160],"of":[161,183,201],"PSOT":[162],"during":[163],"optimization.":[164],"Across":[165],"multiple":[166],"LLM":[167],"families,":[168],"InfoQuant":[169],"consistently":[170],"outperforms":[171],"prior":[172],"PTQ":[173],"end-to-end":[175],"training":[176],"baselines.":[177],"Under":[178],"W4A4KV4,":[179],"it":[180],"preserves":[181],"97%":[182],"floating-point":[184],"accuracy":[185],"on":[186],"average":[187],"reduces":[189],"LLaMA-2":[191],"13B":[192],"performance":[193],"gap":[194],"42%":[196],"over":[197],"previous":[199],"state":[200],"art.":[203],"Code":[204],"available":[206],"at":[207],"[https://github.com/LLIKKE/InfoQuant](https://github.com/LLIKKE/InfoQuant)":[208]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-28T00:00:00"}
