{"id":"https://openalex.org/W4416037845","doi":"https://doi.org/10.18653/v1/2025.emnlp-demos.32","title":"CafGa: Customizing Feature Attributions to Explain Language Models","display_name":"CafGa: Customizing Feature Attributions to Explain Language Models","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4416037845","doi":"https://doi.org/10.18653/v1/2025.emnlp-demos.32"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2025.emnlp-demos.32","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.emnlp-demos.32","pdf_url":"https://aclanthology.org/2025.emnlp-demos.32.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: System Demonstrations","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.emnlp-demos.32.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5107589250","display_name":"Alan David Boyle","orcid":null},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":true,"raw_author_name":"Alan David Boyle","raw_affiliation_strings":["ETH Zurich"],"affiliations":[{"raw_affiliation_string":"ETH Zurich","institution_ids":["https://openalex.org/I35440088"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073000458","display_name":"Furui Cheng","orcid":"https://orcid.org/0000-0003-2329-6126"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Furui Cheng","raw_affiliation_strings":["ETH Zurich"],"affiliations":[{"raw_affiliation_string":"ETH Zurich","institution_ids":["https://openalex.org/I35440088"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074912324","display_name":"Vil\u00e9m Zouhar","orcid":null},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Vil\u00e9m Zouhar","raw_affiliation_strings":["ETH Zurich"],"affiliations":[{"raw_affiliation_string":"ETH Zurich","institution_ids":["https://openalex.org/I35440088"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020415668","display_name":"Mennatallah El\u2010Assady","orcid":"https://orcid.org/0000-0001-8526-2613"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Mennatallah El-Assady","raw_affiliation_strings":["ETH Zurich"],"affiliations":[{"raw_affiliation_string":"ETH Zurich","institution_ids":["https://openalex.org/I35440088"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5107589250"],"corresponding_institution_ids":["https://openalex.org/I35440088"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18766169,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"461","last_page":"470"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.3147999942302704,"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/T10028","display_name":"Topic Modeling","score":0.3147999942302704,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.2702000141143799,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.09309999644756317,"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/feature","display_name":"Feature (linguistics)","score":0.544700026512146},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4302999973297119},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.3734999895095825},{"id":"https://openalex.org/keywords/language-identification","display_name":"Language identification","score":0.32269999384880066},{"id":"https://openalex.org/keywords/modeling-language","display_name":"Modeling language","score":0.2865999937057495},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.2865999937057495}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5999000072479248},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.544700026512146},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5340999960899353},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5141000151634216},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4302999973297119},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.3734999895095825},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.3273000121116638},{"id":"https://openalex.org/C129792486","wikidata":"https://www.wikidata.org/wiki/Q1050419","display_name":"Language identification","level":3,"score":0.32269999384880066},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.2865999937057495},{"id":"https://openalex.org/C179603123","wikidata":"https://www.wikidata.org/wiki/Q1941921","display_name":"Modeling language","level":3,"score":0.2865999937057495},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.2757999897003174},{"id":"https://openalex.org/C101814296","wikidata":"https://www.wikidata.org/wiki/Q5439685","display_name":"Feature model","level":3,"score":0.27250000834465027},{"id":"https://openalex.org/C143299363","wikidata":"https://www.wikidata.org/wiki/Q900584","display_name":"Attribution","level":2,"score":0.2614000141620636},{"id":"https://openalex.org/C527412718","wikidata":"https://www.wikidata.org/wiki/Q855395","display_name":"Interpretation (philosophy)","level":2,"score":0.25459998846054077}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.emnlp-demos.32","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.emnlp-demos.32","pdf_url":"https://aclanthology.org/2025.emnlp-demos.32.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: System Demonstrations","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.emnlp-demos.32","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.emnlp-demos.32","pdf_url":"https://aclanthology.org/2025.emnlp-demos.32.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: System Demonstrations","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416037845.pdf","grobid_xml":"https://content.openalex.org/works/W4416037845.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Feature":[0],"attribution":[1,37,76],"methods,":[2,38],"such":[3],"as":[4,43,119],"SHAP":[5],"and":[6,53,73,87,91,133],"LIME,":[7],"explain":[8,25],"machine":[9],"learning":[10],"model":[11],"predictions":[12],"by":[13,126],"quantifying":[14],"the":[15,33,89,136,139],"influence":[16],"of":[17,102,138],"each":[18],"input":[19],"component.When":[20],"applying":[21],"feature":[22,36,75],"attributions":[23],"to":[24,55,123],"language":[26],"models,":[27],"a":[28,97],"basic":[29],"question":[30],"is":[31,46],"defining":[32],"interpretable":[34],"components.Traditional":[35],"commonly":[39],"treat":[40],"individual":[41],"words":[42],"atomic":[44],"units.This":[45],"highly":[47],"computationally":[48],"inefficient":[49],"for":[50,71,94],"longform":[51],"text":[52],"fails":[54],"capture":[56],"semantic":[57],"information":[58],"that":[59],"spans":[60],"multiple":[61],"words.To":[62],"address":[63],"this,":[64],"we":[65,105],"present":[66],"CafGa,":[67],"an":[68],"interactive":[69],"tool":[70],"generating":[72],"evaluating":[74],"explanations":[77],"at":[78],"customizable":[79],"granularities.CafGa":[80],"supports":[81],"customized":[82],"segmentation":[83],"with":[84],"user":[85,98],"interaction":[86],"visualizes":[88],"deletion":[90],"insertion":[92],"curves":[93],"explanation":[95],"assessments.Through":[96],"study":[99],"involving":[100],"participants":[101],"various":[103],"expertise,":[104],"confirm":[106],"CafGa's":[107],"usefulness,":[108],"particularly":[109],"among":[110],"LLM":[111],"practitioners.Explanations":[112],"created":[113],"using":[114],"CafGa":[115],"were":[116],"also":[117],"perceived":[118],"more":[120],"useful":[121],"compared":[122],"those":[124],"generated":[125],"two":[127],"fully":[128],"automatic":[129],"baseline":[130],"methods:":[131],"Parti-tionSHAP":[132],"MExGen,":[134],"suggesting":[135],"effectiveness":[137],"system.":[140]},"counts_by_year":[],"updated_date":"2026-03-07T13:37:22.277990","created_date":"2025-11-08T00:00:00"}