{"id":"https://openalex.org/W7140306610","doi":"https://doi.org/10.48550/arxiv.2603.22706","title":"How Far Can VLMs Go for Visual Bug Detection? Studying 19,738 Keyframes from 41 Hours of Gameplay Videos","display_name":"How Far Can VLMs Go for Visual Bug Detection? Studying 19,738 Keyframes from 41 Hours of Gameplay Videos","publication_year":2026,"publication_date":"2026-03-24","ids":{"openalex":"https://openalex.org/W7140306610","doi":"https://doi.org/10.48550/arxiv.2603.22706"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.22706","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.22706","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":"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.2603.22706","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130610939","display_name":"Wentao Lu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Wentao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114042924","display_name":"A. I. Senchenko","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Senchenko, Alexander","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130542274","display_name":"Alan Sayle","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sayle, Alan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130582029","display_name":"Abram Hindle","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hindle, Abram","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5130576310","display_name":"Cor-Paul Bezemer","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bezemer, Cor-Paul","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/T11439","display_name":"Video Analysis and Summarization","score":0.2969000041484833,"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/T11439","display_name":"Video Analysis and Summarization","score":0.2969000041484833,"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/T10260","display_name":"Software Engineering Research","score":0.09960000216960907,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.09130000323057175,"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/correctness","display_name":"Correctness","score":0.7982000112533569},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4684000015258789},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.45239999890327454},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.41280001401901245},{"id":"https://openalex.org/keywords/visual-reasoning","display_name":"Visual reasoning","score":0.37130001187324524},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.3695000112056732},{"id":"https://openalex.org/keywords/visual-attention","display_name":"Visual attention","score":0.36230000853538513}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8475000262260437},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.7982000112533569},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5375999808311462},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4684000015258789},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.4560000002384186},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.45239999890327454},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.41280001401901245},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3797000050544739},{"id":"https://openalex.org/C2777508537","wikidata":"https://www.wikidata.org/wiki/Q7936620","display_name":"Visual reasoning","level":2,"score":0.37130001187324524},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.3695000112056732},{"id":"https://openalex.org/C2986089797","wikidata":"https://www.wikidata.org/wiki/Q6501338","display_name":"Visual attention","level":3,"score":0.36230000853538513},{"id":"https://openalex.org/C168065819","wikidata":"https://www.wikidata.org/wiki/Q845566","display_name":"Debugging","level":2,"score":0.35030001401901245},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.3409999907016754},{"id":"https://openalex.org/C3018412434","wikidata":"https://www.wikidata.org/wiki/Q7889","display_name":"Video game","level":2,"score":0.3400000035762787},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3336000144481659},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.3183000087738037},{"id":"https://openalex.org/C158495155","wikidata":"https://www.wikidata.org/wiki/Q2369151","display_name":"Visual search","level":2,"score":0.2662000060081482},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.2612999975681305},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2606000006198883},{"id":"https://openalex.org/C170130773","wikidata":"https://www.wikidata.org/wiki/Q216378","display_name":"Usability","level":2,"score":0.25850000977516174}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.22706","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.22706","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":"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.2603.22706","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.22706","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":"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":[{"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth","score":0.6740215420722961}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Video-based":[0],"quality":[1],"assurance":[2],"(QA)":[3],"for":[4,14,38],"long-form":[5],"gameplay":[6,74,91,200],"video":[7,44],"is":[8],"labor-intensive":[9],"and":[10,18,34,93,115,143,160,178,213],"error-prone,":[11],"yet":[12],"valuable":[13],"assessing":[15],"game":[16],"stability":[17],"visual":[19,31,40,57,196,214],"correctness":[20],"over":[21,169],"extended":[22],"play":[23],"sessions.":[24],"Vision":[25],"language":[26],"models":[27],"(VLMs)":[28],"promise":[29],"general-purpose":[30],"reasoning":[32],"capabilities":[33],"thus":[35],"appear":[36],"attractive":[37],"detecting":[39,56,191],"bugs":[41,197],"directly":[42],"from":[43,89,104],"frames.":[45],"Recent":[46],"benchmarks":[47],"suggest":[48],"that":[49,139,184,209],"VLMs":[50,80,186],"can":[51],"achieve":[52],"promising":[53],"results":[54],"in":[55,82,198],"glitches":[58],"on":[59,63],"curated":[60],"datasets.":[61],"Building":[62],"these":[64,163],"findings,":[65],"we":[66],"conduct":[67],"a":[68,95,101,105,111,135,192],"real-world":[69],"study":[70,86],"using":[71],"industrial":[72],"QA":[73,199],"videos":[75,92],"to":[76,128],"evaluate":[77],"how":[78],"well":[79],"perform":[81],"practical":[83],"scenarios.":[84],"Our":[85,181],"samples":[87],"keyframes":[88],"long":[90],"asks":[94],"VLM":[96,130,141],"whether":[97],"each":[98],"keyframe":[99],"contains":[100],"bug.":[102],"Starting":[103],"single-prompt":[106],"baseline,":[107,172],"the":[108,148,170],"model":[109,138],"achieves":[110],"precision":[112],"of":[113,118,150,190,195],"0.50":[114],"an":[116],"accuracy":[117],"0.72.":[119],"We":[120],"then":[121],"examine":[122],"two":[123],"common":[124],"enhancement":[125],"strategies":[126,164],"used":[127],"improve":[129],"performance":[131],"without":[132],"fine-tuning:":[133],"(1)":[134],"secondary":[136],"judge":[137],"re-evaluates":[140],"outputs,":[142],"(2)":[144],"metadata-augmented":[145],"prompting":[146],"through":[147],"retrieval":[149],"prior":[151],"bug":[152],"reports.":[153],"Across":[154],"\\textbf{100":[155],"videos}":[156],"totaling":[157],"\\textbf{41":[158],"hours}":[159],"\\textbf{19,738":[161],"keyframes},":[162],"provide":[165],"only":[166],"marginal":[167],"improvements":[168],"simple":[171],"while":[173],"introducing":[174],"additional":[175],"computational":[176],"cost":[177],"output":[179],"variance.":[180],"findings":[182],"indicate":[183],"off-the-shelf":[185],"are":[187],"already":[188],"capable":[189],"certain":[193],"range":[194],"videos,":[201],"but":[202],"further":[203],"progress":[204],"likely":[205],"requires":[206],"hybrid":[207],"approaches":[208],"better":[210],"separate":[211],"textual":[212],"anomaly":[215],"detection.":[216]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-26T00:00:00"}