{"id":"https://openalex.org/W7163535113","doi":"https://doi.org/10.48550/arxiv.2606.04046","title":"Dive into the Scene: Breaking the Perceptual Bottleneck in Vision-Language Decision Making via Focus Plan Generation","display_name":"Dive into the Scene: Breaking the Perceptual Bottleneck in Vision-Language Decision Making via Focus Plan Generation","publication_year":2026,"publication_date":"2026-06-02","ids":{"openalex":"https://openalex.org/W7163535113","doi":"https://doi.org/10.48550/arxiv.2606.04046"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.04046","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.04046","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2606.04046","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100771371","display_name":"Bo Xiao","orcid":"https://orcid.org/0000-0001-5294-1118"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiao, Boyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137842331","display_name":"Bohong Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Bohong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137904213","display_name":"Yumeng Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yumeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137858864","display_name":"Ji Feng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Feng, Ji","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045601793","display_name":"Yao-Xiang Ding","orcid":"https://orcid.org/0000-0001-8580-1103"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ding, Yao-Xiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137909987","display_name":"Kun Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Kun","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":0.8870999813079834,"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":0.8870999813079834,"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":0.014499999582767487,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.012500000186264515,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.673799991607666},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.5893999934196472},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.564300000667572},{"id":"https://openalex.org/keywords/embodied-cognition","display_name":"Embodied cognition","score":0.5088000297546387},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.450300008058548},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.44780001044273376},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.43290001153945923},{"id":"https://openalex.org/keywords/plan","display_name":"Plan (archaeology)","score":0.39079999923706055},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.38119998574256897}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7364000082015991},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.673799991607666},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.5893999934196472},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.564300000667572},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5307999849319458},{"id":"https://openalex.org/C100609095","wikidata":"https://www.wikidata.org/wiki/Q1335050","display_name":"Embodied cognition","level":2,"score":0.5088000297546387},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4593999981880188},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.450300008058548},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.44780001044273376},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.43290001153945923},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.42989999055862427},{"id":"https://openalex.org/C2776505523","wikidata":"https://www.wikidata.org/wiki/Q4785468","display_name":"Plan (archaeology)","level":2,"score":0.39079999923706055},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.38119998574256897},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.37439998984336853},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.37220001220703125},{"id":"https://openalex.org/C178253425","wikidata":"https://www.wikidata.org/wiki/Q162668","display_name":"Visual perception","level":3,"score":0.3244999945163727},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.321399986743927},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.31859999895095825},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.31839999556541443},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3131999969482422},{"id":"https://openalex.org/C143587482","wikidata":"https://www.wikidata.org/wiki/Q1543216","display_name":"Iterative and incremental development","level":2,"score":0.31279999017715454},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.3012000024318695},{"id":"https://openalex.org/C160145156","wikidata":"https://www.wikidata.org/wiki/Q778586","display_name":"Executable","level":2,"score":0.2619999945163727},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2612000107765198},{"id":"https://openalex.org/C158495155","wikidata":"https://www.wikidata.org/wiki/Q2369151","display_name":"Visual search","level":2,"score":0.25929999351501465},{"id":"https://openalex.org/C108154423","wikidata":"https://www.wikidata.org/wiki/Q1469792","display_name":"Salience (neuroscience)","level":2,"score":0.2529999911785126}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.04046","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.04046","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2606.04046","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.04046","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":[{"score":0.8087435364723206,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0,62],"embodied":[1,175],"vision-language":[2],"decision":[3],"making":[4],"tasks":[5,196],"such":[6],"as":[7],"robotic":[8],"manipulation":[9],"and":[10,13,66,152,189,202],"navigation,":[11],"Vision-Language":[12],"Vision-Language-Action":[14],"Models":[15],"(VLMs":[16],"&":[17],"VLAs)":[18],"are":[19,26,33,204],"powerful":[20],"tools":[21],"with":[22],"different":[23],"benefits:":[24],"VLMs":[25,120,188],"better":[27,34],"at":[28,35],"long-term":[29,123],"planning,":[30],"while":[31,71,191],"VLAs":[32],"reactive":[36,156],"control.":[37],"However,":[38,94],"their":[39,122],"performance":[40],"is":[41,76,86],"limited":[42],"by":[43],"the":[44,53,77,140,166],"same":[45],"perceptual":[46],"bottleneck:":[47],"visual":[48,184],"hallucinations":[49,185],"arise":[50],"due":[51],"to":[52,56,79,91,133],"models'":[54],"inability":[55],"distinguish":[57],"task-relevant":[58],"objects":[59,70],"from":[60],"distractors.":[61],"principle,":[63],"accurate":[64],"identification":[65],"focus":[67,101,115,168],"on":[68,173],"critical":[69],"filtering":[72],"out":[73],"irrelevant":[74],"ones":[75],"key":[78],"break":[80],"this":[81,95,108],"limitation.":[82],"A":[83],"straightforward":[84],"solution":[85],"one-step":[87],"focus:":[88],"directly":[89],"attending":[90],"essential":[92],"objects.":[93],"approach":[96],"proves":[97],"ineffective":[98],"because":[99],"effective":[100],"inherently":[102],"requires":[103],"deep":[104],"scene":[105,131],"understanding.":[106],"To":[107,154],"end,":[109],"we":[110,158],"propose":[111],"SceneDiver,":[112],"a":[113,129,161],"coarse-to-fine":[114],"plan":[116],"generation":[117],"method":[118,181],"for":[119,164,186],"leveraging":[121],"planning":[124],"abilities,":[125],"that":[126,179],"first":[127],"constructs":[128],"holistic":[130],"graph":[132],"establish":[134],"initial":[135],"comprehension,":[136],"then":[137],"progressively":[138],"decomposes":[139],"task":[141],"into":[142,170],"simpler":[143],"sub-problems":[144],"through":[145],"an":[146],"iterative":[147],"cycle":[148],"of":[149],"recognition,":[150],"understanding,":[151],"analysis.":[153],"enable":[155],"control,":[157],"also":[159],"design":[160],"lightweight":[162],"adapter":[163],"distilling":[165],"deliberate":[167],"ability":[169],"VLAs.":[171],"Evaluations":[172],"standard":[174],"AI":[176],"benchmarks":[177],"confirm":[178],"our":[180],"substantially":[182],"reduces":[183],"both":[187],"VLAs,":[190],"preserving":[192],"computational":[193],"efficiency":[194],"in":[195],"requiring":[197],"fast":[198],"execution.":[199],"Our":[200],"code":[201],"data":[203],"released":[205],"at:":[206],"https://future-item.github.io/SceneDiver.":[207]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-05T00:00:00"}