{"id":"https://openalex.org/W7164017582","doi":"https://doi.org/10.48550/arxiv.2606.09248","title":"Temporal-Aware Reasoning Optimization for Video Temporal Grounding","display_name":"Temporal-Aware Reasoning Optimization for Video Temporal Grounding","publication_year":2026,"publication_date":"2026-06-08","ids":{"openalex":"https://openalex.org/W7164017582","doi":"https://doi.org/10.48550/arxiv.2606.09248"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.09248","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.09248","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.2606.09248","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5071596230","display_name":"Minghang Zheng","orcid":"https://orcid.org/0000-0003-1612-975X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Minghang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138217957","display_name":"Zihao Yin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yin, Zihao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138201790","display_name":"Yi Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Yi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138274522","display_name":"Yuxin Peng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peng, Yuxin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138266510","display_name":"Yang Liu (4829)","orcid":"https://orcid.org/0009-0000-6987-875X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yang","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":0.9901000261306763,"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":0.9901000261306763,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.0010000000474974513,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.0010000000474974513,"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/reasoning-system","display_name":"Reasoning system","score":0.6351000070571899},{"id":"https://openalex.org/keywords/correctness","display_name":"Correctness","score":0.5685999989509583},{"id":"https://openalex.org/keywords/opportunistic-reasoning","display_name":"Opportunistic reasoning","score":0.5138999819755554},{"id":"https://openalex.org/keywords/visual-reasoning","display_name":"Visual reasoning","score":0.5026000142097473},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.49869999289512634},{"id":"https://openalex.org/keywords/deductive-reasoning","display_name":"Deductive reasoning","score":0.4706000089645386},{"id":"https://openalex.org/keywords/qualitative-reasoning","display_name":"Qualitative reasoning","score":0.42480000853538513},{"id":"https://openalex.org/keywords/psychology-of-reasoning","display_name":"Psychology of reasoning","score":0.4246000051498413},{"id":"https://openalex.org/keywords/commonsense-reasoning","display_name":"Commonsense reasoning","score":0.40689998865127563}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7218000292778015},{"id":"https://openalex.org/C89288958","wikidata":"https://www.wikidata.org/wiki/Q7301504","display_name":"Reasoning system","level":2,"score":0.6351000070571899},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.5685999989509583},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5670999884605408},{"id":"https://openalex.org/C86827895","wikidata":"https://www.wikidata.org/wiki/Q7098582","display_name":"Opportunistic reasoning","level":4,"score":0.5138999819755554},{"id":"https://openalex.org/C2777508537","wikidata":"https://www.wikidata.org/wiki/Q7936620","display_name":"Visual reasoning","level":2,"score":0.5026000142097473},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.49869999289512634},{"id":"https://openalex.org/C97364631","wikidata":"https://www.wikidata.org/wiki/Q484284","display_name":"Deductive reasoning","level":2,"score":0.4706000089645386},{"id":"https://openalex.org/C83725634","wikidata":"https://www.wikidata.org/wiki/Q7268699","display_name":"Qualitative reasoning","level":2,"score":0.42480000853538513},{"id":"https://openalex.org/C183521366","wikidata":"https://www.wikidata.org/wiki/Q7256422","display_name":"Psychology of reasoning","level":4,"score":0.4246000051498413},{"id":"https://openalex.org/C193221554","wikidata":"https://www.wikidata.org/wiki/Q5153664","display_name":"Commonsense reasoning","level":2,"score":0.40689998865127563},{"id":"https://openalex.org/C37335422","wikidata":"https://www.wikidata.org/wiki/Q6888134","display_name":"Model-based reasoning","level":3,"score":0.4041000008583069},{"id":"https://openalex.org/C36964233","wikidata":"https://www.wikidata.org/wiki/Q7920942","display_name":"Verbal reasoning","level":3,"score":0.39649999141693115},{"id":"https://openalex.org/C103057564","wikidata":"https://www.wikidata.org/wiki/Q4751139","display_name":"Analytic reasoning","level":3,"score":0.3946000039577484},{"id":"https://openalex.org/C159032336","wikidata":"https://www.wikidata.org/wiki/Q2488768","display_name":"Non-monotonic logic","level":2,"score":0.3898000121116638},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.38260000944137573},{"id":"https://openalex.org/C2778701210","wikidata":"https://www.wikidata.org/wiki/Q28130034","display_name":"Constructive","level":3,"score":0.3815000057220459},{"id":"https://openalex.org/C107848011","wikidata":"https://www.wikidata.org/wiki/Q4680756","display_name":"Adaptive reasoning","level":4,"score":0.37389999628067017},{"id":"https://openalex.org/C20162079","wikidata":"https://www.wikidata.org/wiki/Q1151406","display_name":"Case-based reasoning","level":2,"score":0.3709999918937683},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.35679998993873596},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.35109999775886536},{"id":"https://openalex.org/C115086926","wikidata":"https://www.wikidata.org/wiki/Q17004651","display_name":"Causal reasoning","level":3,"score":0.3368000090122223},{"id":"https://openalex.org/C155911833","wikidata":"https://www.wikidata.org/wiki/Q3817354","display_name":"Spatial intelligence","level":2,"score":0.33489999175071716},{"id":"https://openalex.org/C195344581","wikidata":"https://www.wikidata.org/wiki/Q2555318","display_name":"Automated reasoning","level":2,"score":0.321399986743927},{"id":"https://openalex.org/C43971567","wikidata":"https://www.wikidata.org/wiki/Q3142865","display_name":"Logical reasoning","level":2,"score":0.31200000643730164},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28610000014305115},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.25839999318122864}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.09248","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.09248","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.2606.09248","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.09248","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":[{"display_name":"Quality Education","score":0.6337910890579224,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Multi-modal":[0],"Large":[1],"Language":[2],"Models":[3],"(MLLMs)":[4],"have":[5],"achieved":[6],"remarkable":[7],"progress":[8],"in":[9,97,147],"video":[10],"temporal":[11,33],"grounding":[12],"with":[13,78],"reinforcement":[14],"learning":[15],"for":[16,31],"generating":[17],"reasoning":[18,56,94,113,121,139,152,162,180],"paths.":[19],"However,":[20],"existing":[21],"models":[22],"often":[23],"produce":[24],"superficial":[25],"reasoning,":[26],"which":[27,170],"offers":[28],"limited":[29],"guidance":[30],"precise":[32],"localization.":[34],"This":[35],"limitation":[36],"stems":[37],"from":[38],"(1)":[39],"inefficient":[40],"random":[41],"exploration":[42,105,187],"and":[43,101,128,182],"(2)":[44],"reward":[45,175],"functions":[46],"that":[47,70,87,198],"focus":[48],"solely":[49],"on":[50,203],"the":[51,73,131,148,151,190],"answer":[52],"correctness":[53],"while":[54],"ignoring":[55],"quality.":[57,163],"To":[58],"address":[59],"these":[60],"issues,":[61],"we":[62,81,115],"propose":[63],"TaRO":[64,165,199],"(Temporal-Aware":[65],"Reasoning":[66,85],"Optimization),":[67],"a":[68,83,117,145,159,167,185],"framework":[69],"explicitly":[71],"enhances":[72],"model's":[74],"ability":[75],"of":[76,106,150,161],"thinking":[77,135],"time.":[79],"First,":[80],"introduce":[82],"Constructive":[84],"Exploration":[86],"leverages":[88],"pre-generated":[89],"dense":[90],"captions":[91],"to":[92,111,125,144,176,184],"construct":[93],"paths":[95],"grounded":[96],"explicit":[98],"visual":[99],"cues":[100],"timestamps,":[102],"enabling":[103],"efficient":[104],"high-quality":[107],"time-aware":[108],"reasoning.":[109,195],"Second,":[110],"evaluate":[112],"quality,":[114],"design":[116],"Temporal-Sensitivity":[118],"Reward.":[119],"High-quality":[120],"should":[122,140],"be":[123],"anchored":[124],"specific":[126],"events":[127],"timestamps.":[129],"If":[130],"event":[132],"boundary":[133],"under":[134],"is":[136,207],"disrupted,":[137],"such":[138],"become":[141],"invalid,":[142],"leading":[143],"drop":[146,157],"logit":[149],"path.":[153],"We":[154],"utilize":[155],"this":[156,174],"as":[158],"critique":[160],"Finally,":[164],"follows":[166],"progressive":[168],"curriculum,":[169],"starts":[171],"by":[172],"utilizing":[173],"select":[177],"better":[178],"constructed":[179],"paths,":[181],"evolves":[183],"free":[186],"phase":[188],"where":[189],"model":[191],"autonomously":[192],"generates":[193],"effective":[194],"Experiments":[196],"demonstrate":[197],"achieves":[200],"state-of-the-art":[201],"performance":[202],"VTG":[204],"benchmarks.":[205],"Code":[206],"available":[208],"at":[209],"https://github.com/oceanflowlab/TaRO.":[210]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-10T00:00:00"}