{"id":"https://openalex.org/W7164997542","doi":"https://doi.org/10.48550/arxiv.2606.17118","title":"MODE: Modality-Decomposed Expert-Level Mixed-Precision Quantization for MoE Multimodal LLMs","display_name":"MODE: Modality-Decomposed Expert-Level Mixed-Precision Quantization for MoE Multimodal LLMs","publication_year":2026,"publication_date":"2026-06-15","ids":{"openalex":"https://openalex.org/W7164997542","doi":"https://doi.org/10.48550/arxiv.2606.17118"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.17118","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.17118","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":null,"license_id":null,"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.2606.17118","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138821699","display_name":"Yuanteng Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Yuanteng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138801806","display_name":"Peisong Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Peisong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055459279","display_name":"Zhilei Liu","orcid":"https://orcid.org/0000-0003-1447-6256"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Zhilei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124907855","display_name":"Nanxin Zeng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zeng, Nanxin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007937132","display_name":"Yuantian Shao","orcid":"https://orcid.org/0000-0003-1116-6252"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shao, Yuantian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134108072","display_name":"Shiqiang Lang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lang, Shiqiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138764460","display_name":"Tao Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Tao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138828654","display_name":"Chuangyi Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Chuangyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138784925","display_name":"Qinghao Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Qinghao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138823600","display_name":"Gang Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Gang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138759121","display_name":"Jing Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Jing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138771608","display_name":"Jian Cheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cheng, Jian","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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.2946999967098236,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.2946999967098236,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.12890000641345978,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.07569999992847443,"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":0.6805999875068665},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.36070001125335693},{"id":"https://openalex.org/keywords/skew","display_name":"Skew","score":0.35670000314712524},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.3312000036239624},{"id":"https://openalex.org/keywords/vector-quantization","display_name":"Vector quantization","score":0.3224000036716461},{"id":"https://openalex.org/keywords/masking","display_name":"Masking (illustration)","score":0.29820001125335693}],"concepts":[{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.6805999875068665},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5958999991416931},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44609999656677246},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.36070001125335693},{"id":"https://openalex.org/C43711488","wikidata":"https://www.wikidata.org/wiki/Q7534783","display_name":"Skew","level":2,"score":0.35670000314712524},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.34279999136924744},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.3312000036239624},{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.3224000036716461},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2992999851703644},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.29820001125335693},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.29010000824928284},{"id":"https://openalex.org/C41045048","wikidata":"https://www.wikidata.org/wiki/Q202843","display_name":"Linear programming","level":2,"score":0.2833000123500824},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.27230000495910645},{"id":"https://openalex.org/C56086750","wikidata":"https://www.wikidata.org/wiki/Q6042592","display_name":"Integer programming","level":2,"score":0.2563000023365021},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25609999895095825}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.17118","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.17118","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.17118","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.17118","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Mixture-of-Experts":[0],"Multimodal":[1],"Large":[2],"Language":[3],"Models":[4],"(MoE-MLLMs)":[5],"offer":[6],"remarkable":[7],"performance":[8,171],"but":[9],"incur":[10],"prohibitive":[11],"GPU":[12],"memory":[13],"costs,":[14],"making":[15],"compression":[16],"essential.":[17],"Among":[18],"PTQ":[19],"methods,":[20],"expert-level":[21,105],"mixed-precision":[22,106],"quantization":[23,107,130],"has":[24],"proven":[25],"effective":[26],"for":[27,93,109,167],"MoE-LLMs,":[28],"yet":[29],"suffers":[30],"notable":[31],"degradation":[32],"on":[33],"MoE-MLLMs":[34,110],"due":[35],"to":[36,59,70,122,138,151,173],"two":[37],"overlooked":[38],"biases":[39],"in":[40],"expert":[41,56,113],"importance":[42],"estimation.":[43,140],"(1)":[44],"At":[45],"the":[46,49,71,76,79,182],"cross-modal":[47],"level,":[48,78],"numerical":[50],"dominance":[51],"of":[52,82],"vision":[53,63,84,120],"tokens":[54,85,121],"causes":[55],"selection":[57,114],"frequency":[58,88,115],"be":[60],"dominated":[61],"by":[62,116],"tokens,":[64],"masking":[65],"experts":[66,91],"that":[67,111,162],"are":[68,143],"critical":[69,92],"text":[72],"modality;":[73],"(2)":[74],"at":[75,176,181],"intra-vision":[77],"large":[80],"proportion":[81],"redundant":[83,119],"further":[86,128],"skew":[87],"statistics,":[89],"obscuring":[90],"informative":[94],"visual":[95,125],"content.":[96],"To":[97],"bridge":[98],"gaps,":[99],"we":[100],"propose":[101],"MODE,":[102],"a":[103,135,156],"modality-decomposed":[104],"framework":[108],"decomposes":[112],"modality,":[117],"filters":[118],"obtain":[123],"denoised":[124],"frequency,":[126],"and":[127],"evaluates":[129],"sensitivity":[131],"per":[132],"modality":[133],"as":[134],"complementary":[136],"signal":[137],"frequency-based":[139],"These":[141],"signals":[142],"integrated":[144],"into":[145],"an":[146],"Integer":[147],"Linear":[148],"Programming":[149],"formulation":[150],"assign":[152],"per-expert":[153],"bit-widths":[154],"under":[155],"given":[157],"budget.":[158],"Extensive":[159],"experiments":[160],"show":[161],"MODE":[163],"is":[164],"particularly":[165],"well-suited":[166],"MoE-MLLMs,":[168],"limiting":[169],"average":[170],"loss":[172],"within":[174],"2.9%":[175],"W3A16,":[177],"with":[178],"larger":[179],"gains":[180],"extreme":[183],"2-bit":[184],"setting.":[185]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-18T00:00:00"}