{"id":"https://openalex.org/W7164047164","doi":"https://doi.org/10.48550/arxiv.2606.07607","title":"Position: Genomic Model Research Must Move Beyond Anecdotal Evaluation of Interpretability Methods","display_name":"Position: Genomic Model Research Must Move Beyond Anecdotal Evaluation of Interpretability Methods","publication_year":2026,"publication_date":"2026-05-29","ids":{"openalex":"https://openalex.org/W7164047164","doi":"https://doi.org/10.48550/arxiv.2606.07607"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.07607","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.07607","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,"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.2606.07607","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138267889","display_name":"Shasha Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Shasha","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138209549","display_name":"Mingyu Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Mingyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138274234","display_name":"Ke Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Ke","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":0.23469999432563782,"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":0.23469999432563782,"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/T11642","display_name":"Genomics and Rare Diseases","score":0.14229999482631683,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.07760000228881836,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.947700023651123},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.6710000038146973},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.4332999885082245},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.34630000591278076},{"id":"https://openalex.org/keywords/predictive-power","display_name":"Predictive power","score":0.30219998955726624}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.947700023651123},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6863999962806702},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.6710000038146973},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5699999928474426},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5493000149726868},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.49380001425743103},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.4332999885082245},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.34630000591278076},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.34130001068115234},{"id":"https://openalex.org/C2778136018","wikidata":"https://www.wikidata.org/wiki/Q10350689","display_name":"Predictive power","level":2,"score":0.30219998955726624},{"id":"https://openalex.org/C539667460","wikidata":"https://www.wikidata.org/wiki/Q2414942","display_name":"Management science","level":1,"score":0.2903999984264374},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.2824999988079071},{"id":"https://openalex.org/C201797286","wikidata":"https://www.wikidata.org/wiki/Q4914986","display_name":"Biological data","level":2,"score":0.2524000108242035}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.07607","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.07607","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,"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.2606.07607","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.07607","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,"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":0.7258156538009644,"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":{"Advances":[0],"in":[1],"machine":[2,31],"learning":[3,32],"and":[4,63,107,138,154,169],"computational":[5],"power":[6],"have":[7,35],"unlocked":[8],"the":[9,13,25,52,79,97,113],"predictive":[10],"potential":[11],"of":[12,55,81,120,151,171],"human":[14],"genome,":[15],"yet":[16],"biologists":[17],"now":[18],"demand":[19],"that":[20,86],"these":[21],"models":[22],"also":[23],"elucidate":[24],"underlying":[26],"biological":[27,155],"mechanisms.":[28],"While":[29],"interpretable":[30],"(IML)":[33],"techniques":[34],"been":[36,45],"increasingly":[37],"applied":[38],"to":[39,102,110,129,165],"bridge":[40],"this":[41],"gap,":[42],"there":[43],"has":[44],"a":[46,59,70,125,162],"pervasive":[47],"reliance":[48],"on":[49,58,73],"anecdotal":[50],"validation:":[51],"vast":[53],"majority":[54],"research":[56],"relies":[57],"single":[60],"IML":[61,88,173],"method":[62],"reports":[64],"only":[65],"isolated":[66],"successful":[67],"instances.":[68],"Through":[69],"benchmarking":[71],"study":[72],"transcription":[74],"factor":[75],"binding,":[76],"we":[77,122,160],"demonstrate":[78],"risks":[80],"current":[82],"practices.":[83],"We":[84],"show":[85],"different":[87],"methods":[89],"can":[90],"often":[91],"(1)":[92],"yield":[93],"contradictory":[94],"explanations":[95],"for":[96,124],"same":[98],"predictions,":[99],"(2)":[100],"fail":[101,109],"localize":[103],"known":[104],"regulatory":[105],"motifs,":[106],"(3)":[108],"faithfully":[111],"reflect":[112],"model's":[114],"internal":[115],"decision":[116],"process.":[117],"In":[118],"light":[119],"this,":[121,159],"argue":[123],"validation":[126],"framework":[127,164],"analogous":[128],"clinical":[130],"trials:":[131],"just":[132],"as":[133],"trials":[134],"require":[135],"rigorous":[136,167],"design":[137],"adverse-event":[139],"reporting,":[140],"genomic":[141,172],"interpretability":[142],"must":[143],"move":[144],"beyond":[145],"cherry-picked":[146],"plausibility":[147],"toward":[148],"systematic":[149],"assessment":[150],"consistency,":[152],"faithfulness,":[153],"validity.":[156],"To":[157],"facilitate":[158],"propose":[161],"tiered":[163],"guide":[166],"evaluation":[168],"reporting":[170],"methods.":[174]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-10T00:00:00"}