{"id":"https://openalex.org/W7141088124","doi":"https://doi.org/10.48550/arxiv.2603.25004","title":"Interpretable Zero-shot Referring Expression Comprehension with Query-driven Scene Graphs","display_name":"Interpretable Zero-shot Referring Expression Comprehension with Query-driven Scene Graphs","publication_year":2026,"publication_date":"2026-03-26","ids":{"openalex":"https://openalex.org/W7141088124","doi":"https://doi.org/10.48550/arxiv.2603.25004"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.25004","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.25004","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":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.2603.25004","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130808804","display_name":"Yike Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Yike","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021857737","display_name":"Necva B\u00f6l\u00fcc\u00fc","orcid":"https://orcid.org/0000-0001-8121-3048"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bolucu, Necva","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008748003","display_name":"Stephen Wan","orcid":"https://orcid.org/0000-0001-7505-1417"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wan, Stephen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030655287","display_name":"Dadong Wang","orcid":"https://orcid.org/0000-0002-0188-7833"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Dadong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073686641","display_name":"Jiahao Xia","orcid":"https://orcid.org/0000-0001-9628-9563"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xia, Jiahao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5130759504","display_name":"Jian Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Jian","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":0.9976999759674072,"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":0.9976999759674072,"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":0.00019999999494757503,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.00019999999494757503,"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":0.8167999982833862},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.6378999948501587},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6261000037193298},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.585099995136261},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.499099999666214},{"id":"https://openalex.org/keywords/comprehension","display_name":"Comprehension","score":0.47690001130104065},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.44679999351501465},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.44589999318122864},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.43540000915527344},{"id":"https://openalex.org/keywords/scene-graph","display_name":"Scene graph","score":0.4343999922275543}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8167999982833862},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.792900025844574},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7019000053405762},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.6378999948501587},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6261000037193298},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6039000153541565},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.585099995136261},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.499099999666214},{"id":"https://openalex.org/C511192102","wikidata":"https://www.wikidata.org/wiki/Q5156948","display_name":"Comprehension","level":2,"score":0.47690001130104065},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.44679999351501465},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.44589999318122864},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.43540000915527344},{"id":"https://openalex.org/C179372163","wikidata":"https://www.wikidata.org/wiki/Q1406181","display_name":"Scene graph","level":3,"score":0.4343999922275543},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4108000099658966},{"id":"https://openalex.org/C86034646","wikidata":"https://www.wikidata.org/wiki/Q474311","display_name":"Semantic gap","level":4,"score":0.3718000054359436},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.3546000123023987},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3343999981880188},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33309999108314514},{"id":"https://openalex.org/C90559484","wikidata":"https://www.wikidata.org/wiki/Q778379","display_name":"Expression (computer science)","level":2,"score":0.33079999685287476},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3278000056743622},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.3221000134944916},{"id":"https://openalex.org/C2777508537","wikidata":"https://www.wikidata.org/wiki/Q7936620","display_name":"Visual reasoning","level":2,"score":0.321399986743927},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.31690001487731934},{"id":"https://openalex.org/C25810664","wikidata":"https://www.wikidata.org/wiki/Q44325","display_name":"Ontology","level":2,"score":0.3000999987125397},{"id":"https://openalex.org/C149106765","wikidata":"https://www.wikidata.org/wiki/Q1982453","display_name":"Denotation (semiotics)","level":3,"score":0.2978000044822693},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.2921000123023987},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.2696000039577484},{"id":"https://openalex.org/C2779439875","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Natural language understanding","level":3,"score":0.2694000005722046},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.26809999346733093},{"id":"https://openalex.org/C2780103172","wikidata":"https://www.wikidata.org/wiki/Q1309721","display_name":"Visual Objects","level":3,"score":0.26499998569488525},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.2508000135421753},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.25}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.25004","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.25004","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":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.2603.25004","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.25004","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.5461922883987427,"display_name":"Quality Education","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":{"Zero-shot":[0],"referring":[1],"expression":[2],"comprehension":[3],"(REC)":[4],"aims":[5],"to":[6,52,73,112,129],"locate":[7],"target":[8,158],"objects":[9],"in":[10,84,180],"images":[11],"given":[12,131],"natural":[13],"language":[14],"queries":[15,44],"without":[16],"relying":[17],"on":[18,192],"task-specific":[19],"training":[20],"data,":[21],"demanding":[22],"strong":[23,210],"visual":[24,55,76,211],"understanding":[25,149],"capabilities.":[26],"Existing":[27],"Vision-Language":[28],"Models~(VLMs),":[29],"such":[30],"as":[31,103],"CLIP,":[32],"commonly":[33],"address":[34],"zero-shot":[35,96,194],"REC":[36,85,97,195],"by":[37,151,166],"directly":[38,74],"measuring":[39],"feature":[40],"similarities":[41],"between":[42,142],"textual":[43,79,163],"and":[45,57,125,146,204],"image":[46,144],"regions.":[47],"However,":[48],"these":[49,89],"methods":[50],"struggle":[51],"capture":[53],"fine-grained":[54],"details":[56],"understand":[58],"complex":[59],"object":[60,126,159],"relationships.":[61],"Meanwhile,":[62],"Large":[63],"Language":[64],"Models~(LLMs)":[65],"excel":[66],"at":[67],"high-level":[68],"semantic":[69,148],"reasoning,":[70],"their":[71,82],"inability":[72],"abstract":[75],"features":[77],"into":[78],"semantics":[80],"limits":[81],"application":[83],"tasks.":[86],"To":[87],"overcome":[88],"limitations,":[90],"we":[91,107,138],"propose":[92],"\\textbf{SGREC},":[93],"an":[94,154],"interpretable":[95],"method":[98],"leveraging":[99,134],"query-driven":[100,115],"scene":[101,116,136,168,212],"graphs":[102],"structured":[104,162],"intermediaries.":[105],"Specifically,":[106],"first":[108],"employ":[109],"a":[110,114],"VLM":[111],"construct":[113],"graph":[117],"that":[118,177,187],"explicitly":[119],"encodes":[120],"spatial":[121],"relationships,":[122],"descriptive":[123],"captions,":[124],"interactions":[127],"relevant":[128],"the":[130,140,157,161,167,181],"query.":[132],"By":[133],"this":[135],"graph,":[137,169],"bridge":[139],"gap":[141],"low-level":[143],"regions":[145],"higher-level":[147],"required":[150],"LLMs.":[152],"Finally,":[153],"LLM":[155],"infers":[156],"from":[160],"representation":[164],"provided":[165],"responding":[170],"with":[171],"detailed":[172],"explanations":[173],"for":[174],"its":[175,209],"decisions":[176],"ensure":[178],"interpretability":[179],"inference":[182],"process.":[183],"Extensive":[184],"experiments":[185],"show":[186],"SGREC":[188],"achieves":[189],"top-1":[190],"accuracy":[191],"most":[193],"benchmarks,":[196],"including":[197],"RefCOCO":[198],"val":[199,206],"(66.78\\%),":[200],"RefCOCO+":[201],"testB":[202],"(53.43\\%),":[203],"RefCOCOg":[205],"(73.28\\%),":[207],"highlighting":[208],"understanding.":[213]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-28T00:00:00"}