{"id":"https://openalex.org/W7101776249","doi":"https://doi.org/10.48550/arxiv.2510.23515","title":"FreeFuse: Multi-Subject LoRA Fusion via Adaptive Token-Level Routing at Test Time","display_name":"FreeFuse: Multi-Subject LoRA Fusion via Adaptive Token-Level Routing at Test Time","publication_year":2025,"publication_date":"2025-10-27","ids":{"openalex":"https://openalex.org/W7101776249","doi":"https://doi.org/10.48550/arxiv.2510.23515"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2510.23515","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2510.23515","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2510.23515","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Liu, Yaoli","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Liu, Yaoli","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Ding, Yao-Xiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ding, Yao-Xiang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Zhou, Kun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Kun","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"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":true,"primary_topic":{"id":"https://openalex.org/T10431","display_name":"Ethnobotanical and Medicinal Plants Studies","score":0.03909999877214432,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10431","display_name":"Ethnobotanical and Medicinal Plants Studies","score":0.03909999877214432,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T13124","display_name":"Chemical synthesis and alkaloids","score":0.02410000003874302,"subfield":{"id":"https://openalex.org/subfields/1605","display_name":"Organic Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10895","display_name":"Species Distribution and Climate Change","score":0.017000000923871994,"subfield":{"id":"https://openalex.org/subfields/2302","display_name":"Ecological Modeling"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5291000008583069},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4724000096321106},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4699000120162964},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.46399998664855957},{"id":"https://openalex.org/keywords/routing","display_name":"Routing (electronic design automation)","score":0.44850000739097595},{"id":"https://openalex.org/keywords/identity","display_name":"Identity (music)","score":0.4343999922275543},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.37700000405311584},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.36489999294281006},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.35280001163482666}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8019999861717224},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5291000008583069},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4724000096321106},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4699000120162964},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.46399998664855957},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.44850000739097595},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4449000060558319},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.4343999922275543},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.37700000405311584},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3677999973297119},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.36489999294281006},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36039999127388},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.35280001163482666},{"id":"https://openalex.org/C2778712577","wikidata":"https://www.wikidata.org/wiki/Q3505966","display_name":"Retraining","level":2,"score":0.34630000591278076},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.33079999685287476},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.31279999017715454},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.31060001254081726},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.31029999256134033},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.2924000024795532},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.290800005197525},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2680000066757202},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2669999897480011},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.2662999927997589},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.2615000009536743},{"id":"https://openalex.org/C173414695","wikidata":"https://www.wikidata.org/wiki/Q5510276","display_name":"Fusion mechanism","level":4,"score":0.26089999079704285},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.25839999318122864},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.25619998574256897},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2547999918460846}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2510.23515","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2510.23515","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":"doi:10.48550/arxiv.2510.23515","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2510.23515","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":"article"},"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":{"This":[0],"paper":[1],"proposes":[2],"FreeFuse,":[3],"a":[4,75],"training-free":[5],"framework":[6],"for":[7,59,104],"multi-subject":[8],"text-to-image":[9],"generation":[10],"through":[11,110],"automatic":[12],"fusion":[13],"of":[14],"multiple":[15],"subject":[16,40,129],"LoRAs.":[17],"In":[18],"contrast":[19],"to":[20,28,43,86,91,132],"prior":[21],"studies":[22],"that":[23,35,77,142],"focus":[24],"on":[25],"retraining":[26],"LoRA":[27],"alleviate":[29],"feature":[30],"conflicts,":[31],"our":[32],"analysis":[33],"reveals":[34],"simply":[36],"spatially":[37],"confining":[38],"the":[39,69,79,102],"LoRA's":[41],"output":[42],"its":[44],"target":[45],"region":[46],"and":[47,151],"preventing":[48],"other":[49],"LoRAs":[50],"from":[51],"directly":[52],"intruding":[53],"into":[54,136],"this":[55],"area":[56],"is":[57,156],"sufficient":[58],"effective":[60],"mitigation.":[61],"Accordingly,":[62],"we":[63],"implement":[64],"Adaptive":[65],"Token-Level":[66],"Routing":[67],"during":[68],"inference":[70],"phase.":[71],"We":[72],"introduce":[73],"FreeFuseAttn,":[74],"mechanism":[76],"exploits":[78],"flow":[80],"matching":[81],"model's":[82],"intrinsic":[83],"semantic":[84],"alignment":[85],"dynamically":[87],"match":[88],"subject-specific":[89],"tokens":[90],"their":[92],"corresponding":[93],"spatial":[94,123],"regions":[95],"at":[96,158],"early":[97],"denoising":[98],"timesteps,":[99],"thereby":[100],"bypassing":[101],"need":[103,126],"external":[105],"segmentors.":[106],"FreeFuse":[107,143],"distinguishes":[108],"itself":[109],"high":[111],"practicality:":[112],"it":[113],"necessitates":[114],"no":[115],"additional":[116],"training,":[117],"model":[118],"modifications,":[119],"or":[120],"user-defined":[121],"masks":[122],"conditions.":[124],"Users":[125],"only":[127],"provide":[128],"activation":[130],"words":[131],"achieve":[133],"seamless":[134],"integration":[135],"standard":[137],"workflows.":[138],"Extensive":[139],"experiments":[140],"validate":[141],"outperforms":[144],"existing":[145],"approaches":[146],"in":[147],"both":[148],"identity":[149],"preservation":[150],"compositional":[152],"fidelity.":[153],"Our":[154],"code":[155],"available":[157],"https://github.com/yaoliliu/FreeFuse.":[159]},"counts_by_year":[],"updated_date":"2026-02-01T03:34:12.195049","created_date":"2025-10-29T00:00:00"}
