{"id":"https://openalex.org/W7135181793","doi":"https://doi.org/10.48550/arxiv.2603.11447","title":"Enhancing Lightweight Vision Language Models through Group Competitive Learning for Socially Compliant Navigation","display_name":"Enhancing Lightweight Vision Language Models through Group Competitive Learning for Socially Compliant Navigation","publication_year":2026,"publication_date":"2026-03-12","ids":{"openalex":"https://openalex.org/W7135181793","doi":"https://doi.org/10.48550/arxiv.2603.11447"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.11447","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.11447","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.2603.11447","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129038007","display_name":"Xinyu Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Xinyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063403718","display_name":"Atsushi Konno","orcid":"https://orcid.org/0000-0003-3288-8844"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Konno, Atsushi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129034963","display_name":"Toshihiko Yamasaki","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yamasaki, Toshihiko","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129072165","display_name":"Ling Xiao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiao, Ling","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":0.852400004863739,"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":0.852400004863739,"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/T10709","display_name":"Social Robot Interaction and HRI","score":0.08020000159740448,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.014499999582767487,"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/semantics","display_name":"Semantics (computer science)","score":0.608299970626831},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.4489000141620636},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4259999990463257},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.40149998664855957},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.3944999873638153},{"id":"https://openalex.org/keywords/computational-model","display_name":"Computational model","score":0.3783999979496002},{"id":"https://openalex.org/keywords/competitive-advantage","display_name":"Competitive advantage","score":0.31839999556541443},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.30079999566078186},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.2971999943256378}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6513000130653381},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.608299970626831},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5515999794006348},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.4489000141620636},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4259999990463257},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.40149998664855957},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.3944999873638153},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.3783999979496002},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36809998750686646},{"id":"https://openalex.org/C58546491","wikidata":"https://www.wikidata.org/wiki/Q1150207","display_name":"Competitive advantage","level":2,"score":0.31839999556541443},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.30079999566078186},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2971999943256378},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.29660001397132874},{"id":"https://openalex.org/C91306197","wikidata":"https://www.wikidata.org/wiki/Q45767","display_name":"Competition (biology)","level":2,"score":0.2937000095844269},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.28279998898506165},{"id":"https://openalex.org/C2779439875","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Natural language understanding","level":3,"score":0.27730000019073486},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.2759000062942505},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.27309998869895935},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.27239999175071716},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.26739999651908875},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.26409998536109924},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.2639000117778778},{"id":"https://openalex.org/C2781311116","wikidata":"https://www.wikidata.org/wiki/Q83306","display_name":"Group (periodic table)","level":2,"score":0.26330000162124634},{"id":"https://openalex.org/C145460709","wikidata":"https://www.wikidata.org/wiki/Q859951","display_name":"Human\u2013robot interaction","level":3,"score":0.2517000138759613}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.11447","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.11447","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.2603.11447","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.11447","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":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.44897425174713135}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Social":[0],"robot":[1],"navigation":[2,125],"requires":[3],"a":[4,83],"sophisticated":[5],"integration":[6],"of":[7,90,118,149],"scene":[8],"semantics":[9,104],"and":[10,23,55,67,141,151,155,206],"human":[11],"social":[12,124],"norms.":[13],"Scaling":[14],"up":[15],"Vision":[16],"Language":[17],"Models":[18],"(VLMs)":[19],"generally":[20],"improves":[21],"reasoning":[22,54,65],"decision-making":[24,56],"capabilities":[25,89],"for":[26,40,201],"socially":[27,59],"compliant":[28],"navigation.":[29],"However,":[30,179],"increased":[31],"model":[32,119,140,169,174,185],"size":[33],"incurs":[34],"substantial":[35],"computational":[36,207],"overhead,":[37],"limiting":[38],"suitability":[39],"real-time":[41],"robotic":[42],"deployment.":[43,211],"Conversely,":[44],"lightweight":[45,91],"VLMs":[46],"enable":[47],"efficient":[48],"inference":[49],"but":[50],"often":[51],"exhibit":[52],"weaker":[53],"performance":[57],"in":[58,209],"complex":[60],"environments.":[61],"Achieving":[62],"both":[63,203],"strong":[64],"ability":[66],"efficiency":[68,208],"remains":[69],"an":[70,146,198],"open":[71],"challenge.":[72],"To":[73],"bridge":[74],"this":[75],"gap,":[76],"we":[77],"propose":[78],"Group":[79,97,110],"Competitive":[80,98],"Learning":[81],"(GCL),":[82],"strategy":[84,94],"designed":[85],"to":[86,101,113,144],"amplify":[87],"the":[88,96,115,137,167,172,181,183,188],"VLMs.":[92],"Our":[93],"introduces":[95],"Objective":[99],"(GCO)":[100],"harmonize":[102],"global":[103],"with":[105],"distributional":[106],"regularization,":[107],"alongside":[108],"Asymmetric":[109],"Optimization":[111],"(AGO)":[112],"explore":[114],"upper":[116],"limits":[117],"performance.":[120,133],"Empirical":[121],"evaluations":[122],"on":[123],"benchmarks":[126],"demonstrate":[127],"that":[128,195],"GCL":[129,135,196],"significantly":[130],"elevates":[131],"VLM":[132],"Specifically,":[134],"enables":[136],"Qwen2.5-VL-3B":[138],"learner":[139],"guide":[142],"Qwen3-VL-4B":[143],"achieve":[145],"F1":[147],"score":[148],"0.968":[150],"0.914,":[152],"representing":[153],"40\\%":[154],"12\\%":[156],"improvement":[157],"over":[158],"vanilla":[159,165],"supervised":[160],"fine-tuning":[161],"(SFT).":[162],"Notably,":[163],"under":[164],"SFT,":[166],"3B":[168,184],"initially":[170],"trails":[171],"8B":[173,189],"(F1:":[175],"0.692":[176],"vs.":[177],"0.755).":[178],"through":[180],"GCL,":[182],"outperforms":[186],"(28\\%)":[187],"baseline":[190],"model.":[191],"These":[192],"results":[193],"suggest":[194],"provides":[197],"effective":[199],"solution":[200],"achieving":[202],"high":[204],"accuracy":[205],"real-world":[210]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-03-14T00:00:00"}
