{"id":"https://openalex.org/W7155068072","doi":"https://doi.org/10.48550/arxiv.2604.17475","title":"Waking Up Blind: Cold-Start Optimization of Supervision-Free Agentic Trajectories for Grounded Visual Perception","display_name":"Waking Up Blind: Cold-Start Optimization of Supervision-Free Agentic Trajectories for Grounded Visual Perception","publication_year":2026,"publication_date":"2026-04-19","ids":{"openalex":"https://openalex.org/W7155068072","doi":"https://doi.org/10.48550/arxiv.2604.17475"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.17475","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.17475","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":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.2604.17475","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5124005971","display_name":"Ashutosh Bajpai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bajpai, Ashutosh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134197281","display_name":"Tamal Majumder","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Majumder, Tamal","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134209029","display_name":"Akshay Nambi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nambi, Akshay","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134188620","display_name":"Tanmoy Chakraborty","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chakraborty, Tanmoy","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":0.8865000009536743,"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":0.8865000009536743,"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":0.02070000022649765,"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":0.01640000008046627,"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/task","display_name":"Task (project management)","score":0.6712999939918518},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.534500002861023},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.5214999914169312},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5209000110626221},{"id":"https://openalex.org/keywords/task-analysis","display_name":"Task analysis","score":0.4146000146865845},{"id":"https://openalex.org/keywords/visual-perception","display_name":"Visual perception","score":0.4000000059604645},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.39910000562667847},{"id":"https://openalex.org/keywords/preference","display_name":"Preference","score":0.3882000148296356}],"concepts":[{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6712999939918518},{"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":0.5831000208854675},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.551800012588501},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.534500002861023},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.5214999914169312},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5209000110626221},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.49219998717308044},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.4146000146865845},{"id":"https://openalex.org/C178253425","wikidata":"https://www.wikidata.org/wiki/Q162668","display_name":"Visual perception","level":3,"score":0.4000000059604645},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.39910000562667847},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.3882000148296356},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.36640000343322754},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.32919999957084656},{"id":"https://openalex.org/C111370547","wikidata":"https://www.wikidata.org/wiki/Q7451120","display_name":"Sensory cue","level":2,"score":0.3156999945640564},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3109000027179718},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.30399999022483826},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.2922999858856201},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.2818000018596649},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.27320000529289246},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.25200000405311584},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.25130000710487366}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.17475","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.17475","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":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.2604.17475","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.17475","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":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":{"Small":[0],"Vision-Language":[1],"Models":[2],"(SVLMs)":[3],"are":[4],"efficient":[5,156],"task":[6,91,143],"controllers":[7],"but":[8],"often":[9],"suffer":[10],"from":[11,162],"visual":[12,80],"brittleness":[13],"and":[14,95,132,149],"poor":[15],"tool":[16,71,96,120,150],"orchestration.":[17],"They":[18],"typically":[19],"require":[20],"expensive":[21],"supervised":[22],"trajectory":[23],"tuning":[24],"to":[25,68,100,118,147],"mitigate":[26],"these":[27],"deficits.":[28],"In":[29],"this":[30],"work,":[31],"we":[32],"propose":[33],"Self-supervised":[34],"Perception":[35],"Enabled":[36],"by":[37,145,152],"Cascaded":[38],"Tool":[39,111],"Rollout":[40],"Alignment":[41],"(SPECTRA),":[42],"a":[43,62,84,115],"supervision-free":[44],"framework":[45],"that":[46,65,88,137,159],"bootstraps":[47],"agentic":[48,140],"capabilities":[49],"via":[50],"Coldstart":[51],"Reinforcement":[52],"Learning":[53],"for":[54],"SVLMs.":[55],"SPECTRA":[56,138],"enforces":[57],"Soft":[58],"Structured":[59],"Multi-turn":[60],"Rollouts,":[61],"topological":[63],"constraint":[64],"directs":[66],"agents":[67,158],"explicitly":[69],"sequence":[70],"derived":[72],"evidence":[73],"before":[74],"synthesis,":[75],"effectively":[76,161],"grounding":[77],"reasoning":[78],"in":[79,122],"observations.":[81],"We":[82,108],"employ":[83],"multi-objective":[85],"reward":[86],"signal":[87],"simultaneously":[89],"maximizes":[90],"correctness,":[92],"rollout":[93],"structure,":[94],"utility,":[97],"enabling":[98,154],"agent":[99],"self-discover":[101],"robust":[102],"behaviors":[103],"without":[104],"human":[105],"preference":[106],"labels.":[107],"further":[109],"introduce":[110],"Instrumental":[112],"Utility":[113],"(TIU),":[114],"novel":[116],"metric":[117],"quantify":[119],"efficacy":[121],"the":[123],"absence":[124],"of":[125],"ground":[126],"truth.":[127],"Extensive":[128],"evaluations":[129],"across":[130],"composite":[131],"out-of-distribution":[133],"(MMMU-Pro)":[134],"benchmarks":[135],"demonstrate":[136],"boosts":[139],"trajectories,":[141],"improving":[142],"accuracy":[144],"up":[146],"5%":[148],"efficiency":[151],"9%,":[153],"more":[155],"multimodal":[157],"learn":[160],"environmental":[163],"interaction":[164],"alone.":[165]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-04-22T00:00:00"}