{"id":"https://openalex.org/W7161964684","doi":"https://doi.org/10.48550/arxiv.2605.20950","title":"Focus-then-Context: Subject-Centric Progressive Visual Token Reduction for Vision-Language Models","display_name":"Focus-then-Context: Subject-Centric Progressive Visual Token Reduction for Vision-Language Models","publication_year":2026,"publication_date":"2026-05-20","ids":{"openalex":"https://openalex.org/W7161964684","doi":"https://doi.org/10.48550/arxiv.2605.20950"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.20950","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.20950","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.2605.20950","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136683164","display_name":"Yulin Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Yulin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136701927","display_name":"Yun Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Zheng","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":0.4341000020503998,"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":0.4341000020503998,"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":0.27799999713897705,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.11569999903440475,"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/security-token","display_name":"Security token","score":0.6039999723434448},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.5892999768257141},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.5821999907493591},{"id":"https://openalex.org/keywords/human-visual-system-model","display_name":"Human visual system model","score":0.538100004196167},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4781999886035919},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.43380001187324524},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.42160001397132874},{"id":"https://openalex.org/keywords/visual-perception","display_name":"Visual perception","score":0.4092000126838684},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.399399995803833},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.37389999628067017}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7718999981880188},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6152999997138977},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.6039999723434448},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.5892999768257141},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.5821999907493591},{"id":"https://openalex.org/C160086991","wikidata":"https://www.wikidata.org/wiki/Q5939193","display_name":"Human visual system model","level":3,"score":0.538100004196167},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4781999886035919},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4650000035762787},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.43380001187324524},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.42160001397132874},{"id":"https://openalex.org/C178253425","wikidata":"https://www.wikidata.org/wiki/Q162668","display_name":"Visual perception","level":3,"score":0.4092000126838684},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.399399995803833},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.37389999628067017},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3700999915599823},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3573000133037567},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.3555000126361847},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3490000069141388},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.34360000491142273},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.34279999136924744},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.3407999873161316},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.3346000015735626},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.33309999108314514},{"id":"https://openalex.org/C2779668609","wikidata":"https://www.wikidata.org/wiki/Q623092","display_name":"Rapid serial visual presentation","level":3,"score":0.3255000114440918},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.32190001010894775},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.3005000054836273},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.2973000109195709},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.2685000002384186},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.26809999346733093},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.2606000006198883},{"id":"https://openalex.org/C3826847","wikidata":"https://www.wikidata.org/wiki/Q188768","display_name":"FLOPS","level":2,"score":0.25619998574256897},{"id":"https://openalex.org/C2780385302","wikidata":"https://www.wikidata.org/wiki/Q367158","display_name":"Protocol (science)","level":3,"score":0.2524000108242035}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.20950","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.20950","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.2605.20950","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.20950","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":{"Vision-Language":[0],"Models":[1],"(VLMs)":[2],"face":[3],"a":[4,57,77,103,110,168,175],"bottleneck":[5],"of":[6,67,106,138,161],"prohibitive":[7],"computational":[8],"costs":[9],"arising":[10],"from":[11,121],"massive":[12],"visual":[13,32,70,87,98,107,162],"token":[14,20],"sequences":[15],"during":[16],"inference.":[17],"Existing":[18],"vision":[19],"reduction":[21,60,171],"methods":[22],"alleviate":[23],"this":[24,52],"burden,":[25],"but":[26],"they":[27],"unintentionally":[28],"preserve":[29],"the":[30,37,64,68,84,96,135,139],"isolated":[31],"subject":[33,99],"strictly":[34],"aligned":[35],"with":[36,158,174],"user's":[38],"query,":[39],"which":[40],"fails":[41],"to":[42,81,101,117,133,154],"substantially":[43],"explore":[44],"salient":[45],"subjects":[46],"and":[47,89,167],"their":[48],"contextual":[49,119],"relationships.":[50],"In":[51],"paper,":[53],"we":[54,74],"propose":[55],"SPpruner,":[56],"subject-centric":[58],"progressive":[59],"paradigm":[61,147],"that":[62,145],"emulates":[63],"\\textit{Focus-then-Context}":[65],"mechanism":[66],"human":[69],"perception":[71],"system.":[72],"Specifically,":[73],"first":[75],"construct":[76],"focus":[78],"identification":[79],"module":[80,114],"explicitly":[82],"model":[83],"interplay":[85],"between":[86],"saliency":[88],"semantic":[90],"relevance.":[91],"Herein,":[92],"it":[93,126],"can":[94,127],"excavate":[95],"comprehensive":[97],"spectrum":[100],"ensure":[102],"high-fidelity":[104],"representation":[105],"input.":[108],"Subsequently,":[109],"context-aware":[111],"structural":[112,136],"scanning":[113],"is":[115],"developed":[116],"aggregate":[118],"cues":[120],"neighboring":[122],"regions.":[123],"As":[124],"such,":[125],"effectively":[128],"restore":[129],"global":[130],"relational":[131],"dependencies":[132],"uphold":[134],"integrity":[137],"preserved":[140],"subjects.":[141],"Extensive":[142],"experiments":[143],"demonstrate":[144],"our":[146],"consistently":[148],"outperforms":[149],"SOTA":[150],"methods,":[151],"achieving":[152],"up":[153],"2.53":[155],"times":[156],"speedup":[157],"only":[159],"22.2%":[160],"tokens":[163],"retained":[164],"in":[165],"Qwen2.5-VL":[166],"67%":[169],"FLOPs":[170],"on":[172],"LLaVA":[173],"negligible":[176],"0.6%":[177],"accuracy":[178],"drop.":[179]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-22T00:00:00"}