{"id":"https://openalex.org/W7163986129","doi":"https://doi.org/10.48550/arxiv.2606.09826","title":"OmniGameArena: A Unified UE5 Benchmark for VLM Game Agents with Improvement Dynamics","display_name":"OmniGameArena: A Unified UE5 Benchmark for VLM Game Agents with Improvement Dynamics","publication_year":2026,"publication_date":"2026-06-08","ids":{"openalex":"https://openalex.org/W7163986129","doi":"https://doi.org/10.48550/arxiv.2606.09826"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.09826","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.09826","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.2606.09826","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138273504","display_name":"Mingxian Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Mingxian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034240662","display_name":"Shengju Qian","orcid":"https://orcid.org/0000-0002-3386-0336"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qian, Shengju","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138204843","display_name":"Yuqi Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yuqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138203653","display_name":"Yi-Hua Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Yi-Hua","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138258231","display_name":"Yiyu Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yiyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138235883","display_name":"Wei Huang (36889)","orcid":"https://orcid.org/0000-0003-3760-6084"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Wei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014906885","display_name":"Yi Li","orcid":"https://orcid.org/0000-0002-7840-2611"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yitang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138204322","display_name":"Fan Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Fan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138225572","display_name":"Zeyu Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Zeyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138260201","display_name":"Lingting Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Lingting","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138236426","display_name":"Xin Wang (91924)","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Xin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138219029","display_name":"Xiaojuan Qi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qi, Xiaojuan","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":0.3984000086784363,"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":0.3984000086784363,"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/T11574","display_name":"Artificial Intelligence in Games","score":0.18250000476837158,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.10010000318288803,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7954000234603882},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6180999875068665},{"id":"https://openalex.org/keywords/bounded-function","display_name":"Bounded function","score":0.5465999841690063},{"id":"https://openalex.org/keywords/observable","display_name":"Observable","score":0.5264999866485596},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.5213000178337097},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4659999907016754},{"id":"https://openalex.org/keywords/reflection","display_name":"Reflection (computer programming)","score":0.396699994802475},{"id":"https://openalex.org/keywords/game-theory","display_name":"Game theory","score":0.3797000050544739}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7954000234603882},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6607000231742859},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6180999875068665},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.5465999841690063},{"id":"https://openalex.org/C32848918","wikidata":"https://www.wikidata.org/wiki/Q845789","display_name":"Observable","level":2,"score":0.5264999866485596},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.5213000178337097},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4659999907016754},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4490000009536743},{"id":"https://openalex.org/C65682993","wikidata":"https://www.wikidata.org/wiki/Q1056451","display_name":"Reflection (computer programming)","level":2,"score":0.396699994802475},{"id":"https://openalex.org/C177142836","wikidata":"https://www.wikidata.org/wiki/Q44455","display_name":"Game theory","level":2,"score":0.3797000050544739},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.3736000061035156},{"id":"https://openalex.org/C145912823","wikidata":"https://www.wikidata.org/wiki/Q113558","display_name":"Dynamics (music)","level":2,"score":0.36340001225471497},{"id":"https://openalex.org/C41550386","wikidata":"https://www.wikidata.org/wiki/Q529909","display_name":"Multi-agent system","level":2,"score":0.3580000102519989},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.34940001368522644},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3296000063419342},{"id":"https://openalex.org/C2986528223","wikidata":"https://www.wikidata.org/wiki/Q193564","display_name":"Game engine","level":2,"score":0.31520000100135803},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.30489999055862427},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.29170000553131104},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28929999470710754},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.28610000014305115},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.2838999927043915},{"id":"https://openalex.org/C46814582","wikidata":"https://www.wikidata.org/wiki/Q23389","display_name":"Nash equilibrium","level":2,"score":0.2800000011920929},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.2689000070095062},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.2685999870300293},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.2646999955177307}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.09826","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.09826","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.2606.09826","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.09826","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":{"Vision-language":[0],"model":[1],"(VLM)":[2],"agents":[3,16,144,152],"are":[4],"increasingly":[5],"deployed":[6],"in":[7,91],"interactive":[8],"game":[9,12,47],"environments.":[10],"Yet":[11],"benchmarks":[13],"for":[14,36,115,141],"VLM":[15,143],"typically":[17],"report":[18,138],"a":[19,59,93,99],"single":[20],"first-attempt":[21],"score":[22,122],"per":[23],"(agent,":[24,117],"game)":[25,118],"pair,":[26],"focus":[27],"on":[28,49,133,145],"single-agent":[29],"Solo":[30,71],"play,":[31],"and":[32,45,75,82,127,149],"lack":[33],"unified":[34,79],"protocols":[35],"evaluating":[37],"heterogeneous":[38],"agent":[39],"classes":[40],"(commercial":[41],"VLMs,":[42,44],"open-weight":[43],"specialized":[46],"policies)":[48],"the":[50,83,121,129,146],"same":[51],"footing.":[52],"We":[53,137],"address":[54],"these":[55,139],"gaps":[56],"with":[57,78],"OmniGameArena,":[58],"real-time":[60],"benchmark":[61],"of":[62],"twelve":[63,142],"newly":[64],"built":[65],"Unreal":[66],"Engine":[67],"5":[68],"games":[69],"spanning":[70],"(7),":[72],"PvP":[73],"(3),":[74],"Coop":[76],"(2)":[77],"action":[80],"interfaces,":[81],"Improvement":[84],"Dynamics":[85],"Curve":[86],"(IDC),":[87],"an":[88],"agentic-reflection":[89],"harness":[90],"which":[92],"tool-using":[94],"reflector":[95],"LLM":[96],"autonomously":[97],"refines":[98],"bounded":[100],"skill":[101,131],"prompt":[102],"across":[103,124],"multiple":[104],"rounds.":[105],"Beyond":[106],"cold-start":[107,147],"leaderboard":[108,148],"scores,":[109],"IDC":[110],"exposes":[111],"two":[112],"additional":[113],"observables":[114,140],"each":[116],"pair:":[119],"how":[120,128],"evolves":[123],"reflection":[125],"rounds,":[126],"learned":[130],"behaves":[132],"held-out":[134],"task":[135],"variants.":[136],"four":[150],"top":[151],"under":[153],"IDC.":[154]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-10T00:00:00"}