{"id":"https://openalex.org/W7165852878","doi":"https://doi.org/10.48550/arxiv.2606.25306","title":"Physics Question Scene Graph: Fine-grained Evaluation of Physical Plausibility in Text-to-Video Generation","display_name":"Physics Question Scene Graph: Fine-grained Evaluation of Physical Plausibility in Text-to-Video Generation","publication_year":2026,"publication_date":"2026-06-24","ids":{"openalex":"https://openalex.org/W7165852878","doi":"https://doi.org/10.48550/arxiv.2606.25306"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.25306","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.25306","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.2606.25306","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5119770877","display_name":"Atin Pothiraj","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pothiraj, Atin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139321231","display_name":"Jaemin Cho","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cho, Jaemin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139359031","display_name":"Yue Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yue","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038276570","display_name":"Elias Stengel-Eskin","orcid":"https://orcid.org/0000-0002-6689-505X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Stengel-Eskin, Elias","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139357576","display_name":"Mohit Bansal","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bansal, Mohit","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":0.5479999780654907,"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":0.5479999780654907,"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":0.35740000009536743,"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":0.012500000186264515,"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/hierarchy","display_name":"Hierarchy","score":0.5577999949455261},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5227000117301941},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.478300005197525},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.40290001034736633},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.32030001282691956},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.29420000314712524}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7470999956130981},{"id":"https://openalex.org/C31170391","wikidata":"https://www.wikidata.org/wiki/Q188619","display_name":"Hierarchy","level":2,"score":0.5577999949455261},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5227000117301941},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5148000121116638},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.478300005197525},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.40290001034736633},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33980000019073486},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.33730000257492065},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.32030001282691956},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3158999979496002},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.29420000314712524},{"id":"https://openalex.org/C194583477","wikidata":"https://www.wikidata.org/wiki/Q408891","display_name":"Physical law","level":2,"score":0.2849000096321106},{"id":"https://openalex.org/C116672817","wikidata":"https://www.wikidata.org/wiki/Q1454986","display_name":"Physical system","level":2,"score":0.27480000257492065},{"id":"https://openalex.org/C2776187449","wikidata":"https://www.wikidata.org/wiki/Q1513879","display_name":"Natural language generation","level":3,"score":0.2669000029563904},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.26579999923706055}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.25306","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.25306","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.2606.25306","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.25306","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":[{"score":0.8296421766281128,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Video":[0],"generation":[1,145],"models":[2,146,190,228],"are":[3],"increasingly":[4],"capable":[5],"of":[6,27,79,116,119,237],"producing":[7],"realistic":[8],"videos,":[9],"but":[10],"they":[11,233],"still":[12,234],"struggle":[13],"to":[14,64,72],"generate":[15],"videos":[16,59,140],"that":[17,105,186,201,226],"follow":[18],"basic":[19],"physical":[20,36,73,123,196],"laws.":[21],"Compounding":[22],"this":[23,43],"is":[24,108],"a":[25,51,65,76,83,96,132],"lack":[26],"reliable":[28],"granular":[29,114],"evaluation":[30,54],"methods":[31],"for":[32,212],"localizing":[33],"and":[34,70,137,151,173,222],"specifying":[35],"law":[37],"violations":[38],"in":[39,206,240],"videos.":[40],"We":[41,126,183],"address":[42],"by":[44,60,82,88,129,161],"introducing":[45],"Physics":[46],"Question":[47],"Scene":[48],"Graph":[49],"(PQSG),":[50],"hierarchical":[52],"question-based":[53],"pipeline.":[55],"PQSG":[56,98,112,128,187],"evaluates":[57],"generated":[58,81,139],"checking":[61],"their":[62],"faithfulness":[63],"prompt":[66],"across":[67,158],"objects,":[68],"actions,":[69],"adherence":[71],"laws":[74],"using":[75],"graph-based":[77],"hierarchy":[78],"questions":[80,94],"vision-language":[84],"model":[85],"(VLM),":[86],"guided":[87],"high-quality":[89],"in-context":[90],"examples.":[91],"By":[92],"representing":[93],"as":[95],"graph,":[97],"introduces":[99],"logical":[100],"dependencies":[101],"within":[102],"questions,":[103,224,232],"ensuring":[104],"each":[106,155],"query":[107],"contextually":[109],"valid.":[110],"Moreover,":[111],"provides":[113],"assessments":[115],"which":[117],"qualities":[118],"the":[120,167,202],"video":[121,144,156],"violate":[122],"plausibility":[124],"constraints.":[125],"validate":[127],"creating":[130],"FinePhyEval,":[131,164],"dataset":[133],"with":[134,154],"physics-based":[135],"prompts":[136],"corresponding":[138],"from":[141],"diverse":[142],"state-of-the-art":[143],"(Sora":[147],"2,":[148],"Veo":[149],"3,":[150],"Wan":[152,193],"2.1),":[153],"annotated":[157],"multiple":[159],"categories":[160],"humans.":[162],"Using":[163],"we":[165,199,204,215],"measure":[166],"correlation":[168],"between":[169],"PQSG's":[170],"fine-grained":[171],"scores":[172],"human":[174,238],"judgments,":[175],"showing":[176],"higher":[177,191],"overall":[178],"correlations":[179],"than":[180,192],"prior":[181],"work.":[182],"also":[184,209],"find":[185],"ranks":[188],"closed-source":[189],"2.1":[194],"on":[195,220],"realism.":[197],"Lastly,":[198],"show":[200],"annotations":[203],"provide":[205],"FinePhyEval":[207],"can":[208,229],"be":[210],"used":[211],"subtask":[213],"evaluation:":[214],"benchmark":[216],"two":[217],"strong":[218],"VLMs":[219],"generating":[221],"answering":[223,241],"finding":[225],"while":[227],"create":[230],"human-like":[231],"fall":[235],"short":[236],"performance":[239],"them.":[242]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-26T00:00:00"}