{"id":"https://openalex.org/W7133543200","doi":"https://doi.org/10.48550/arxiv.2603.02655","title":"Real-Time Generation of Game Video Commentary with Multimodal LLMs: Pause-Aware Decoding Approaches","display_name":"Real-Time Generation of Game Video Commentary with Multimodal LLMs: Pause-Aware Decoding Approaches","publication_year":2026,"publication_date":"2026-03-03","ids":{"openalex":"https://openalex.org/W7133543200","doi":"https://doi.org/10.48550/arxiv.2603.02655"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.02655","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.02655","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.2603.02655","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128118380","display_name":"Anum Afzal","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Afzal, Anum","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128100953","display_name":"Yuki Saito","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Saito, Yuki","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042127858","display_name":"Hiroya Takamura","orcid":"https://orcid.org/0000-0002-3244-8294"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Takamura, Hiroya","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051961507","display_name":"Katsuhito Sudoh","orcid":"https://orcid.org/0000-0002-2122-9846"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sudoh, Katsuhito","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013050263","display_name":"Shinnosuke Takamichi","orcid":"https://orcid.org/0000-0003-0520-7847"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Takamichi, Shinnosuke","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128120471","display_name":"Graham Neubig","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Neubig, Graham","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128046356","display_name":"Florian Matthes","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Matthes, Florian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5063285759","display_name":"Tatsuya Ishigaki","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ishigaki, Tatsuya","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":0.7886000275611877,"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":0.7886000275611877,"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/T11439","display_name":"Video Analysis and Summarization","score":0.05979999899864197,"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/T10028","display_name":"Topic Modeling","score":0.04399999976158142,"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/decoding-methods","display_name":"Decoding methods","score":0.8044999837875366},{"id":"https://openalex.org/keywords/utterance","display_name":"Utterance","score":0.7512999773025513},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6089000105857849},{"id":"https://openalex.org/keywords/video-game","display_name":"Video game","score":0.5077999830245972},{"id":"https://openalex.org/keywords/implementation","display_name":"Implementation","score":0.4810999929904938},{"id":"https://openalex.org/keywords/duration","display_name":"Duration (music)","score":0.43860000371932983},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.32260000705718994}],"concepts":[{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.8044999837875366},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8001999855041504},{"id":"https://openalex.org/C2775852435","wikidata":"https://www.wikidata.org/wiki/Q258403","display_name":"Utterance","level":2,"score":0.7512999773025513},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6089000105857849},{"id":"https://openalex.org/C3018412434","wikidata":"https://www.wikidata.org/wiki/Q7889","display_name":"Video game","level":2,"score":0.5077999830245972},{"id":"https://openalex.org/C26713055","wikidata":"https://www.wikidata.org/wiki/Q245962","display_name":"Implementation","level":2,"score":0.4810999929904938},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44369998574256897},{"id":"https://openalex.org/C112758219","wikidata":"https://www.wikidata.org/wiki/Q16038819","display_name":"Duration (music)","level":2,"score":0.43860000371932983},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3849000036716461},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3425999879837036},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.32260000705718994},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.3206000030040741},{"id":"https://openalex.org/C2778152352","wikidata":"https://www.wikidata.org/wiki/Q5165061","display_name":"Content (measure theory)","level":2,"score":0.28110000491142273},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.27880001068115234},{"id":"https://openalex.org/C2780910867","wikidata":"https://www.wikidata.org/wiki/Q1952416","display_name":"Multimodality","level":2,"score":0.2782000005245209},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.27300000190734863},{"id":"https://openalex.org/C2776187449","wikidata":"https://www.wikidata.org/wiki/Q1513879","display_name":"Natural language generation","level":3,"score":0.2727000117301941},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.26350000500679016},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.2554999887943268},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.2531000077724457}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.02655","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.02655","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.2603.02655","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.02655","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":[{"id":"https://metadata.un.org/sdg/4","score":0.47746580839157104,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Real-time":[0],"video":[1,169],"commentary":[2,71,140,170],"generation":[3,26,72,117],"provides":[4],"textual":[5],"descriptions":[6],"of":[7,109,127],"ongoing":[8],"events":[9],"in":[10,17,53],"videos.":[11],"It":[12],"supports":[13],"accessibility":[14],"and":[15,23,34,78,90,124,129,148,161],"engagement":[16],"domains":[18],"such":[19],"as":[20],"sports,":[21],"esports,":[22],"livestreaming.":[24],"Commentary":[25],"involves":[27],"two":[28,82],"essential":[29],"decisions:":[30],"what":[31],"to":[32,36,163],"say":[33,37],"when":[35],"it.":[38],"While":[39],"recent":[40],"prompting-based":[41,83],"approaches":[42],"using":[43,150],"multimodal":[44],"large":[45],"language":[46],"models":[47],"(MLLMs)":[48],"have":[49],"shown":[50],"strong":[51],"performance":[52],"content":[54,149],"generation,":[55],"they":[56],"largely":[57],"ignore":[58],"the":[59,100,106,110,134],"timing":[60,103,147],"aspect.":[61],"We":[62,80,153],"investigate":[63],"whether":[64],"in-context":[65],"prompting":[66,151],"alone":[67],"can":[68,138],"support":[69,164],"real-time":[70,168],"that":[73,98,133],"is":[74],"both":[75],"semantically":[76],"relevant":[77],"well-timed.":[79],"propose":[81],"decoding":[84,96,137],"strategies:":[85],"1)":[86],"a":[87,92,155],"fixed-interval":[88],"approach,":[89],"2)":[91],"novel":[93],"dynamic":[94,135],"interval-based":[95,136],"approach":[97],"adjusts":[99],"next":[101],"prediction":[102],"based":[104],"on":[105,122,167],"estimated":[107],"duration":[108],"previous":[111],"utterance.":[112],"Both":[113],"methods":[114],"enable":[115],"pause-aware":[116],"without":[118],"any":[119],"fine-tuning.":[120],"Experiments":[121],"Japanese":[123],"English":[125],"datasets":[126],"racing":[128],"fighting":[130],"games":[131],"show":[132],"generate":[139],"more":[141],"closely":[142],"aligned":[143],"with":[144],"human":[145],"utterance":[146],"alone.":[152],"release":[154],"multilingual":[156],"benchmark":[157],"dataset,":[158],"trained":[159],"models,":[160],"implementations":[162],"future":[165],"research":[166],"generation.":[171]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-03-05T00:00:00"}
