{"id":"https://openalex.org/W7164938514","doi":"https://doi.org/10.48550/arxiv.2606.16137","title":"XAI-Grounded Explanation Generation for Speech Deepfake Detection with Training-Free Multimodal Large Language Models","display_name":"XAI-Grounded Explanation Generation for Speech Deepfake Detection with Training-Free Multimodal Large Language Models","publication_year":2026,"publication_date":"2026-06-15","ids":{"openalex":"https://openalex.org/W7164938514","doi":"https://doi.org/10.48550/arxiv.2606.16137"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.16137","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.16137","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.2606.16137","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138753593","display_name":"Yupei Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yupei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114245462","display_name":"Qiyang Sun","orcid":"https://orcid.org/0009-0001-9228-4543"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Qiyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090578536","display_name":"X . Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Xiaoliang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138723682","display_name":"Chenxi Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Chenxi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001303929","display_name":"Berrak \u015ei\u015fman","orcid":"https://orcid.org/0000-0001-8078-3305"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sisman, Berrak","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138743723","display_name":"Bj\u00f6rn W. Schuller","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Schuller, Bj\u00f6rn W.","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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.6467000246047974,"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"}},"topics":[{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.6467000246047974,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.12620000541210175,"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":0.03550000116229057,"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/heuristic","display_name":"Heuristic","score":0.6635000109672546},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.6396999955177307},{"id":"https://openalex.org/keywords/trustworthiness","display_name":"Trustworthiness","score":0.5845999717712402},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.5016999840736389},{"id":"https://openalex.org/keywords/attribution","display_name":"Attribution","score":0.4652999937534332},{"id":"https://openalex.org/keywords/natural-language-generation","display_name":"Natural language generation","score":0.4526999890804291},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.45239999890327454}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7462999820709229},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.6635000109672546},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.6396999955177307},{"id":"https://openalex.org/C153701036","wikidata":"https://www.wikidata.org/wiki/Q659974","display_name":"Trustworthiness","level":2,"score":0.5845999717712402},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5716999769210815},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5170999765396118},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.5016999840736389},{"id":"https://openalex.org/C143299363","wikidata":"https://www.wikidata.org/wiki/Q900584","display_name":"Attribution","level":2,"score":0.4652999937534332},{"id":"https://openalex.org/C2776187449","wikidata":"https://www.wikidata.org/wiki/Q1513879","display_name":"Natural language generation","level":3,"score":0.4526999890804291},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.45239999890327454},{"id":"https://openalex.org/C2776608160","wikidata":"https://www.wikidata.org/wiki/Q4785462","display_name":"Natural (archaeology)","level":2,"score":0.3953000009059906},{"id":"https://openalex.org/C2983448237","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Language understanding","level":2,"score":0.39410001039505005},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.35589998960494995},{"id":"https://openalex.org/C156325361","wikidata":"https://www.wikidata.org/wiki/Q1152864","display_name":"Grounded theory","level":3,"score":0.3492000102996826},{"id":"https://openalex.org/C155092808","wikidata":"https://www.wikidata.org/wiki/Q182557","display_name":"Computational linguistics","level":2,"score":0.3402000069618225},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.29829999804496765},{"id":"https://openalex.org/C2779439875","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Natural language understanding","level":3,"score":0.28450000286102295},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.2567000091075897}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.16137","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.16137","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.2606.16137","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.16137","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":[{"display_name":"Peace, Justice and strong institutions","score":0.8073331713676453,"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":{"Speech":[0],"deepfake":[1],"detection":[2],"(SDD)":[3],"systems":[4],"require":[5],"trustworthy":[6],"explanations":[7],"for":[8,76],"reliable":[9],"decision-making.":[10],"Existing":[11],"explanation":[12,52,74,83,106],"ways":[13],"mainly":[14],"fall":[15],"into":[16],"two":[17],"categories.":[18],"Traditional":[19],"explainable":[20],"AI":[21],"(XAI),":[22],"such":[23],"as":[24],"gradient-based":[25],"attribution,":[26],"produces":[27,55],"low-level":[28],"attribution":[29],"signals":[30],"tightly":[31],"coupled":[32],"with":[33,89,112],"model":[34,50],"decisions,":[35],"and":[36,57,67,95,108,124],"harder":[37],"to":[38,61,92],"be":[39],"understood":[40],"by":[41,117],"human":[42,122],"than":[43],"natural":[44],"language":[45,49],"explanations.":[46,97],"Meanwhile,":[47],"large":[48],"(LLM)-based":[51],"generation":[53],"often":[54],"generic":[56],"ungrounded":[58],"descriptions":[59],"due":[60],"the":[62,99],"lack":[63],"of":[64],"heuristic":[65],"evidence":[66,88],"task-specific":[68],"supervision,":[69],"stemming":[70],"from":[71],"limited":[72],"grounded":[73,94,105],"datasets":[75],"SDD.":[77],"We":[78],"therefore":[79],"propose":[80],"a":[81,104],"training-free":[82],"framework":[84],"that":[85,110],"integrates":[86],"XAI":[87,113],"multimodal":[90],"LLMs":[91],"generate":[93],"specific":[96],"Using":[98],"PartialSpoof":[100],"dataset,":[101],"we":[102],"construct":[103],"dataset":[107],"show":[109],"methods":[111],"increase":[114],"inside":[115],"accuracy":[116],"over":[118],"45\\%,":[119],"verified":[120],"through":[121],"evaluation":[123],"faithfulness":[125],"checks.":[126]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-17T00:00:00"}
