{"id":"https://openalex.org/W7166115027","doi":"https://doi.org/10.48550/arxiv.2606.27089","title":"TMP: Tree-structured Mixed-policy Pruning for Large-scale Image Generation and Editing","display_name":"TMP: Tree-structured Mixed-policy Pruning for Large-scale Image Generation and Editing","publication_year":2026,"publication_date":"2026-06-25","ids":{"openalex":"https://openalex.org/W7166115027","doi":"https://doi.org/10.48550/arxiv.2606.27089"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.27089","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.27089","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.2606.27089","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5056795737","display_name":"P Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Peizhen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139402101","display_name":"Yang Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017473451","display_name":"Xunsong Li","orcid":"https://orcid.org/0009-0009-5803-6691"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Xunsong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103870133","display_name":"Liu S","orcid":"https://orcid.org/0000-0001-7255-0982"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Songtao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139433579","display_name":"Zewen Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Zewen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123002309","display_name":"Qiangqiang Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Qiangqiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133531300","display_name":"Guotong Guo","orcid":"https://orcid.org/0009-0004-0954-4001"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Guotong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055989433","display_name":"Jupeng Ding","orcid":"https://orcid.org/0000-0002-1761-6448"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ding, Jupeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075553304","display_name":"Yifu Sun","orcid":"https://orcid.org/0000-0003-4924-9387"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Yifu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139420859","display_name":"coopersli","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"coopersli","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139399634","display_name":"Jian Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Jian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139425258","display_name":"Zhao Zhong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhong, Zhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139452043","display_name":"Liefeng Bo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bo, Liefeng","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":0.20900000631809235,"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":0.20900000631809235,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.1370999962091446,"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/T11019","display_name":"Image Enhancement Techniques","score":0.12549999356269836,"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/pruning","display_name":"Pruning","score":0.6456000208854675},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5947999954223633},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5593000054359436},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5192000269889832},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.4052000045776367},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.39010000228881836},{"id":"https://openalex.org/keywords/image-compression","display_name":"Image compression","score":0.3652999997138977},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.35040000081062317}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8029000163078308},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.6456000208854675},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5947999954223633},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5593000054359436},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5192000269889832},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4708000123500824},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.4052000045776367},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39430001378059387},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.39010000228881836},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.3652999997138977},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.365200012922287},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.35040000081062317},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.34450000524520874},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.33480000495910645},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3093000054359436},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3019999861717224},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.3001999855041504},{"id":"https://openalex.org/C2989087649","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Image synthesis","level":3,"score":0.2994000017642975},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.28439998626708984},{"id":"https://openalex.org/C74912251","wikidata":"https://www.wikidata.org/wiki/Q6815727","display_name":"Memory footprint","level":2,"score":0.27459999918937683},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.2653999924659729},{"id":"https://openalex.org/C2776674983","wikidata":"https://www.wikidata.org/wiki/Q545981","display_name":"Image editing","level":3,"score":0.25859999656677246},{"id":"https://openalex.org/C96146094","wikidata":"https://www.wikidata.org/wiki/Q609057","display_name":"Unification","level":2,"score":0.25099998712539673},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.2500999867916107}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.27089","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.27089","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.2606.27089","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.27089","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":[{"score":0.42163556814193726,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Modern":[0],"image":[1,11,51],"generation":[2,114],"model":[3,91,144],"rapidly":[4],"grows":[5],"their":[6,19],"sizes":[7],"to":[8,28,68,99,105,119,171],"meet":[9],"high-fidelity":[10],"synthesis.":[12],"However,":[13],"they":[14],"gradually":[15],"become":[16],"unaffordable":[17],"for":[18],"enormous":[20],"parameter":[21],"consumption":[22],"and":[23,32,54,56,60,72,87,143,155],"computation":[24],"budget":[25],"that":[26,48],"lead":[27],"massive":[29],"resources":[30],"requirement":[31],"gpu":[33],"memory":[34],"footprint.":[35],"In":[36],"this":[37],"paper,":[38],"we":[39,159],"propose":[40],"TMP,":[41],"the":[42,69,75,121,124,150,161],"first":[43],"Tree-structured":[44],"Mixed-policy":[45],"Pruning":[46],"framework":[47,97],"generalizes":[49],"prevalent":[50],"tasks":[52],"(T2I":[53],"TI2I)":[55],"architectures":[57],"(Mixture-of-Experts":[58],"(MoE)":[59],"Diffusion":[61],"transformer":[62],"(DiT)).":[63],"It":[64],"could":[65],"be":[66],"applied":[67],"step-distilled":[70],"models":[71],"contribute":[73],"as":[74],"last":[76],"stage.":[77],"We":[78,116],"perform":[79],"experiments":[80],"upon":[81],"current":[82],"open-sourced":[83],"SOTA":[84],"HunyuanImage-3.0":[85],"instruct":[86],"a":[88,132],"popular":[89],"efficient":[90],"Z-Image":[92,167],"turbo.":[93],"The":[94,140],"proposed":[95],"pruning":[96],"manages":[98],"compress":[100],"HunyuanImage":[101,129],"3.0":[102,130],"from":[103,169],"80B":[104],"20B":[106,126],"parameters":[107],"at":[108],"75%":[109],"reduction":[110],"ratio,":[111],"sacrificing":[112],"limited":[113],"quality.":[115],"also":[117],"optimize":[118],"enable":[120],"inference":[122,141],"of":[123,128,163],"pruned":[125],"version":[127],"on":[131],"single":[133],"24GB":[134],"4090":[135],"GPU":[136],"by":[137,165],"engineering":[138],"skills.":[139],"script":[142],"weight":[145],"have":[146],"been":[147],"integrated":[148],"into":[149],"existing":[151],"HunyuanImage3.0":[152],"open-source":[153],"github":[154],"huggingface":[156],"repository.":[157],"Besides,":[158],"prove":[160],"efficacy":[162],"TMP":[164],"compressing":[166],"turbo":[168],"6B":[170],"4B":[172],"(33%":[173],"reduction)":[174],"with":[175],"negligible":[176],"degradation.":[177]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-27T00:00:00"}
