{"id":"https://openalex.org/W4415329046","doi":"https://doi.org/10.48550/arxiv.2505.15516","title":"Explainable embeddings with Distance Explainer","display_name":"Explainable embeddings with Distance Explainer","publication_year":2025,"publication_date":"2025-05-21","ids":{"openalex":"https://openalex.org/W4415329046","doi":"https://doi.org/10.48550/arxiv.2505.15516"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2505.15516","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2505.15516","pdf_url":"https://arxiv.org/pdf/2505.15516","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,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2505.15516","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5001300472","display_name":"Christiaan Meijer","orcid":"https://orcid.org/0000-0002-5529-5761","observed_orcids":["https://orcid.org/0000-0002-5529-5761"]},"institutions":[{"id":"https://openalex.org/I4210095242","display_name":"Netherlands eScience Center","ror":"https://ror.org/00rbjv475","country_code":"NL","type":"funder","lineage":["https://openalex.org/I2800991832","https://openalex.org/I4210090210","https://openalex.org/I4210095242"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Meijer, Christiaan","raw_affiliation_strings":["4923.43% distance : 80807 .15% distance : 84561 .44% distance : 84901.04%","Netherlands eScience Center Science Park 402 (Matrix THREE) 1098 XH Amsterdam"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"4923.43% distance : 80807 .15% distance : 84561 .44% distance : 84901.04%","institution_ids":[]},{"raw_affiliation_string":"Netherlands eScience Center Science Park 402 (Matrix THREE) 1098 XH Amsterdam","institution_ids":["https://openalex.org/I4210095242"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012909347","display_name":"Patrick Bos","orcid":"https://orcid.org/0000-0002-6033-960X","observed_orcids":["https://orcid.org/0000-0002-6033-960X"]},"institutions":[{"id":"https://openalex.org/I4210095242","display_name":"Netherlands eScience Center","ror":"https://ror.org/00rbjv475","country_code":"NL","type":"funder","lineage":["https://openalex.org/I2800991832","https://openalex.org/I4210090210","https://openalex.org/I4210095242"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Bos, E. G. Patrick","raw_affiliation_strings":["Netherlands eScience Center Science Park 402 (Matrix THREE) 1098 XH Amsterdam"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Netherlands eScience Center Science Park 402 (Matrix THREE) 1098 XH Amsterdam","institution_ids":["https://openalex.org/I4210095242"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210095242"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":2,"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":1.0,"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":1.0,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.0,"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/T10743","display_name":"Software Testing and Debugging Techniques","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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/explainable-ai","display_name":"explainable AI","score":0.9160000085830688},{"id":"https://openalex.org/keywords/post-hoc-explanation","display_name":"post-hoc explanation","score":0.7450000047683716},{"id":"https://openalex.org/keywords/rise","display_name":"RISE","score":0.7250000238418579},{"id":"https://openalex.org/keywords/selective-masking","display_name":"selective masking","score":0.7369999885559082},{"id":"https://openalex.org/keywords/cross-modal-embeddings","display_name":"cross-modal embeddings","score":0.8410000205039978},{"id":"https://openalex.org/keywords/clip","display_name":"CLIP","score":0.8619999885559082},{"id":"https://openalex.org/keywords/imagenet","display_name":"ImageNet","score":0.6779999732971191},{"id":"https://openalex.org/keywords/faithfulness","display_name":"faithfulness","score":0.8650000095367432},{"id":"https://openalex.org/keywords/explanation-robustness","display_name":"explanation robustness","score":0.6759999990463257}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8978999853134155},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7368000149726868},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6650000214576721},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5741999745368958},{"id":"https://openalex.org/C153701036","wikidata":"https://www.wikidata.org/wiki/Q659974","display_name":"Trustworthiness","level":2,"score":0.48910000920295715},{"id":"https://openalex.org/C2780233690","wikidata":"https://www.wikidata.org/wiki/Q535347","display_name":"Transparency (behavior)","level":2,"score":0.46459999680519104},{"id":"https://openalex.org/C2639959","wikidata":"https://www.wikidata.org/wiki/Q1344778","display_name":"Distance measures","level":2,"score":0.44429999589920044},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.43220001459121704},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4156999886035919},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3628000020980835},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.36149999499320984},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.3481000065803528},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32179999351501465},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.3156000077724457},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.28929999470710754},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2768000066280365},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.2703999876976013},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.266400009393692},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.25609999895095825},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.2533000111579895},{"id":"https://openalex.org/C197947376","wikidata":"https://www.wikidata.org/wiki/Q5155608","display_name":"Comparability","level":2,"score":0.25209999084472656},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.25099998712539673}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2505.15516","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2505.15516","pdf_url":"https://arxiv.org/pdf/2505.15516","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,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2505.15516","doi":"https://doi.org/10.48550/arxiv.2505.15516","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2505.15516","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,"listed_in":[],"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"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2505.15516","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2505.15516","pdf_url":"https://arxiv.org/pdf/2505.15516","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,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4415329046.pdf","grobid_xml":"https://content.openalex.org/works/W4415329046.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W2096733369","https://openalex.org/W2516809705","https://openalex.org/W2616247523","https://openalex.org/W2809136100","https://openalex.org/W2891612330","https://openalex.org/W2948978827","https://openalex.org/W2965211237","https://openalex.org/W3035965352","https://openalex.org/W3082665562","https://openalex.org/W3094502228","https://openalex.org/W3128945589","https://openalex.org/W3129424480","https://openalex.org/W3135367836","https://openalex.org/W3157861865","https://openalex.org/W3187293469","https://openalex.org/W4239025696","https://openalex.org/W4283157935","https://openalex.org/W4321786089","https://openalex.org/W4366262984","https://openalex.org/W4386897466","https://openalex.org/W4389918297","https://openalex.org/W4390897655","https://openalex.org/W4404908721"],"related_works":["https://openalex.org/W4406947280","https://openalex.org/W4389989161","https://openalex.org/W4362654526","https://openalex.org/W2754121484","https://openalex.org/W4414790640","https://openalex.org/W7159689059","https://openalex.org/W4393969960","https://openalex.org/W2942099749","https://openalex.org/W4404181452","https://openalex.org/W4415428631"],"abstract_inverted_index":{"While":[0],"eXplainable":[1],"AI":[2],"(XAI)":[3],"has":[4],"advanced":[5],"significantly,":[6],"few":[7],"methods":[8],"address":[9],"interpretability":[10],"in":[11,35,135,143],"embedded":[12,33,52,105,148],"vector":[13],"spaces":[14,34],"where":[15],"dimensions":[16],"represent":[17],"complex":[18],"abstractions.":[19],"We":[20,66,114],"introduce":[21],"Distance":[22,68],"Explainer,":[23],"a":[24,132],"novel":[25],"method":[26,95],"for":[27],"generating":[28],"local,":[29],"post-hoc":[30],"explanations":[31],"of":[32],"machine":[36],"learning":[37,145],"models.":[38],"Our":[39],"approach":[40],"adapts":[41],"saliency-based":[42],"techniques":[43],"from":[44],"RISE":[45],"to":[46,100],"explain":[47],"the":[48],"distance":[49],"between":[50,104],"two":[51],"data":[53,106],"points":[54,107],"by":[55],"assigning":[56],"attribution":[57],"values":[58],"through":[59],"selective":[60],"masking":[61],"and":[62,74,84,89,112,123,138,141],"distance-ranked":[63],"mask":[64,121],"filtering.":[65],"evaluate":[67],"Explainer":[69],"on":[70],"cross-modal":[71],"embeddings":[72],"(image-image":[73],"image-caption":[75],"pairs)":[76],"using":[77],"established":[78],"XAI":[79,136],"metrics":[80],"including":[81],"Faithfulness,":[82],"Sensitivity/Robustness,":[83],"Randomization.":[85],"Experiments":[86],"with":[87],"ImageNet":[88],"CLIP":[90],"models":[91],"demonstrate":[92],"that":[93],"our":[94],"effectively":[96],"identifies":[97],"features":[98],"contributing":[99],"similarity":[101],"or":[102],"dissimilarity":[103],"while":[108],"maintaining":[109],"high":[110],"robustness":[111],"consistency.":[113],"also":[115],"explore":[116],"how":[117],"parameter":[118],"tuning,":[119],"particularly":[120],"quantity":[122],"selection":[124],"strategy,":[125],"affects":[126],"explanation":[127],"quality.":[128],"This":[129],"work":[130],"addresses":[131],"critical":[133],"gap":[134],"research":[137],"enhances":[139],"transparency":[140],"trustworthiness":[142],"deep":[144],"applications":[146],"utilizing":[147],"spaces.":[149]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2025-10-19T00:00:00"}
