{"id":"https://openalex.org/W7165732007","doi":"https://doi.org/10.48550/arxiv.2606.24759","title":"UniDrive: A Unified Vision-Language and Grounding Framework for Interpretable Risk Understanding in Autonomous Driving","display_name":"UniDrive: A Unified Vision-Language and Grounding Framework for Interpretable Risk Understanding in Autonomous Driving","publication_year":2026,"publication_date":"2026-06-23","ids":{"openalex":"https://openalex.org/W7165732007","doi":"https://doi.org/10.48550/arxiv.2606.24759"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.24759","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.24759","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.2606.24759","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103668258","display_name":"Gao X","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gao, Xiaowei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139301159","display_name":"Pengxiang Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Pengxiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068421344","display_name":"Yitai Cheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cheng, Yitai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139287534","display_name":"Ruihan Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Ruihan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139273439","display_name":"James Haworth","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haworth, James","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055537550","display_name":"Stephen Law","orcid":"https://orcid.org/0000-0003-3184-572X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Law, Stephen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5030866270","display_name":"Y. Ye","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ye, Yun","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":0.9021999835968018,"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":0.9021999835968018,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.020099999383091927,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.012199999764561653,"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/interpretability","display_name":"Interpretability","score":0.8881000280380249},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5698000192642212},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.565500020980835},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.4999000132083893},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.48179998993873596},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.47749999165534973},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4537000060081482},{"id":"https://openalex.org/keywords/ground","display_name":"Ground","score":0.41530001163482666},{"id":"https://openalex.org/keywords/closed-captioning","display_name":"Closed captioning","score":0.4032999873161316}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8881000280380249},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7207000255584717},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.646399974822998},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5698000192642212},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.565500020980835},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.4999000132083893},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.487199991941452},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.48179998993873596},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.47749999165534973},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4537000060081482},{"id":"https://openalex.org/C168993435","wikidata":"https://www.wikidata.org/wiki/Q6501125","display_name":"Ground","level":2,"score":0.41530001163482666},{"id":"https://openalex.org/C157657479","wikidata":"https://www.wikidata.org/wiki/Q2367247","display_name":"Closed captioning","level":3,"score":0.4032999873161316},{"id":"https://openalex.org/C2777508537","wikidata":"https://www.wikidata.org/wiki/Q7936620","display_name":"Visual reasoning","level":2,"score":0.39259999990463257},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.31769999861717224},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.3140000104904175},{"id":"https://openalex.org/C64754055","wikidata":"https://www.wikidata.org/wiki/Q7574053","display_name":"Spatial contextual awareness","level":2,"score":0.3073999881744385},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.30640000104904175},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2800000011920929},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.2705000042915344},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2678999900817871},{"id":"https://openalex.org/C2776010242","wikidata":"https://www.wikidata.org/wiki/Q4677575","display_name":"Active perception","level":3,"score":0.267300009727478},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.26460000872612},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.26339998841285706},{"id":"https://openalex.org/C178253425","wikidata":"https://www.wikidata.org/wiki/Q162668","display_name":"Visual perception","level":3,"score":0.25940001010894775},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2549999952316284}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.24759","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.24759","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.2606.24759","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.24759","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":"Peace, Justice and strong institutions","score":0.6735830903053284,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Recent":[0],"multimodal":[1],"large":[2],"language":[3],"models":[4,48,84],"(MLLMs)":[5],"have":[6],"shown":[7],"strong":[8],"potential":[9],"for":[10,54,70,141,209],"autonomous":[11,75,213],"driving":[12,47,214],"scene":[13,85],"understanding,":[14],"yet":[15],"existing":[16],"methods":[17],"still":[18],"face":[19],"a":[20,64,79,92,111,206],"fundamental":[21],"trade-off":[22],"between":[23],"temporal":[24,80,200],"reasoning":[25,81],"and":[26,67,137,155,161,176,187,189,192,202,211],"spatial":[27,99,124],"precision.":[28],"Models":[29],"that":[30,83,96,150,197],"rely":[31],"on":[32,127,145,172],"single-frame":[33],"or":[34,41],"low-resolution":[35],"inputs":[36],"often":[37],"miss":[38],"small,":[39],"distant,":[40],"partially":[42],"occluded":[43],"hazards,":[44],"while":[45],"language-centric":[46],"frequently":[49],"provide":[50],"limited":[51],"grounded":[52,138],"evidence":[53],"their":[55],"explanations.":[56],"To":[57],"address":[58],"this":[59],"gap,":[60],"we":[61],"propose":[62],"UniDrive,":[63],"unified":[65],"visual-language":[66],"grounding":[68],"framework":[69],"interpretable":[71,210],"risk":[72,135,142],"understanding":[73],"in":[74,158,180],"driving.":[76],"UniDrive":[77,131,151,166],"combines":[78],"branch":[82,95],"dynamics":[86],"from":[87,101],"multi-frame":[88],"visual":[89],"input":[90],"with":[91,122],"high-resolution":[93,203],"perception":[94,204],"preserves":[97],"fine-grained":[98],"details":[100],"the":[102,128,146,168,173],"latest":[103],"frame.":[104],"The":[105,216],"two":[106],"branches":[107],"are":[108],"integrated":[109],"through":[110],"gated":[112],"cross-attention":[113],"fusion":[114],"module,":[115],"enabling":[116],"dynamic":[117],"context":[118],"to":[119,185],"be":[120],"aligned":[121],"precise":[123],"evidence.":[125],"Based":[126],"fused":[129],"representation,":[130],"jointly":[132],"generates":[133],"natural-language":[134],"descriptions":[136],"bounding-box":[139],"outputs":[140],"objects.":[143],"Experiments":[144],"DRAMA-Reasoning":[147],"benchmark":[148],"show":[149],"outperforms":[152],"representative":[153],"image-based":[154],"video-based":[156],"baselines":[157],"both":[159],"captioning":[160],"risk-object":[162],"grounding.":[163],"In":[164],"particular,":[165],"achieves":[167],"best":[169],"overall":[170],"performance":[171],"validation":[174],"split":[175],"demonstrates":[177],"clear":[178],"advantages":[179],"small-object":[181],"localization,":[182],"zero-shot":[183],"generalization":[184],"NuScenes":[186],"BDD100K,":[188],"human-rated":[190],"interpretability":[191],"trustworthiness.":[193],"These":[194],"results":[195],"suggest":[196],"explicitly":[198],"combining":[199],"semantics":[201],"provides":[205],"stronger":[207],"foundation":[208],"safety-oriented":[212],"systems.":[215],"code":[217],"is":[218],"available":[219],"at":[220],"https://github.com/pixeli99/unidrive-dev.":[221]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-25T00:00:00"}