{"id":"https://openalex.org/W7140076560","doi":"https://doi.org/10.48550/arxiv.2603.20101","title":"Pitfalls in Evaluating Interpretability Agents","display_name":"Pitfalls in Evaluating Interpretability Agents","publication_year":2026,"publication_date":"2026-03-20","ids":{"openalex":"https://openalex.org/W7140076560","doi":"https://doi.org/10.48550/arxiv.2603.20101"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.20101","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.20101","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.20101","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5092671619","display_name":"Tal Haklay","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haklay, Tal","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103158458","display_name":"N. Prakash","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Prakash, Nikhil","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130361524","display_name":"Sana Pandey","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pandey, Sana","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085020955","display_name":"Antonio Torralba","orcid":"https://orcid.org/0000-0003-4915-0256"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Torralba, Antonio","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020998070","display_name":"Aaron Mueller","orcid":"https://orcid.org/0009-0005-1148-5001"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mueller, Aaron","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130392524","display_name":"Jacob Andreas","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Andreas, Jacob","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081132390","display_name":"Tamar Rott Shaham","orcid":"https://orcid.org/0000-0002-1455-2266"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shaham, Tamar Rott","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5130401709","display_name":"Yonatan Belinkov","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Belinkov, Yonatan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":8,"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":0.9230999946594238,"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":0.9230999946594238,"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":0.020500000566244125,"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":0.00860000029206276,"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/interpretability","display_name":"Interpretability","score":0.9484999775886536},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6141999959945679},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4799000024795532},{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.47929999232292175},{"id":"https://openalex.org/keywords/interchangeability","display_name":"Interchangeability","score":0.450300008058548},{"id":"https://openalex.org/keywords/complex-system","display_name":"Complex system","score":0.31619998812675476}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.9484999775886536},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6970000267028809},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6141999959945679},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6047999858856201},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.597000002861023},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4799000024795532},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.47929999232292175},{"id":"https://openalex.org/C2779606619","wikidata":"https://www.wikidata.org/wiki/Q17092524","display_name":"Interchangeability","level":2,"score":0.450300008058548},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.32519999146461487},{"id":"https://openalex.org/C47822265","wikidata":"https://www.wikidata.org/wiki/Q854457","display_name":"Complex system","level":2,"score":0.31619998812675476},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.30390000343322754},{"id":"https://openalex.org/C2780626000","wikidata":"https://www.wikidata.org/wiki/Q5936775","display_name":"Human-in-the-loop","level":2,"score":0.29840001463890076},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.29269999265670776},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C2779645999","wikidata":"https://www.wikidata.org/wiki/Q1858477","display_name":"Frugality","level":2,"score":0.25459998846054077}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.20101","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.20101","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.20101","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.20101","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":"article"},"sustainable_development_goals":[{"display_name":"Decent work and economic growth","score":0.7371233105659485,"id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Automated":[0],"interpretability":[1,44,191],"systems":[2,152,192],"aim":[3],"to":[4,14,41,52,56],"reduce":[5],"the":[6,61,73,81,121,123,147,176],"need":[7,51],"for":[8],"human":[9,112,136],"labor":[10],"and":[11,18,63,106,150,193],"scale":[12,53],"analysis":[13,78,118],"increasingly":[15],"large":[16,27],"models":[17,29],"diverse":[19],"tasks.":[20,89],"Recent":[21],"efforts":[22],"toward":[23],"this":[24,70,91],"goal":[25],"leverage":[26],"language":[28],"(LLMs)":[30],"at":[31],"increasing":[32],"levels":[33],"of":[34,65,75,83,133,165,179,197],"autonomy,":[35],"ranging":[36],"from":[37],"fixed":[38],"one-shot":[39],"workflows":[40],"fully":[42],"autonomous":[43],"agents.":[45],"This":[46],"shift":[47],"creates":[48],"a":[49,100],"corresponding":[50],"evaluation":[54,173],"approaches":[55],"keep":[57],"pace":[58],"with":[59],"both":[60],"volume":[62],"complexity":[64],"generated":[66],"explanations.":[67],"We":[68],"investigate":[69],"challenge":[71],"in":[72,98,120,187],"context":[74],"automated":[76,190],"circuit":[77,117],"--":[79],"explaining":[80],"roles":[82],"model":[84,180],"components":[85],"when":[86],"performing":[87],"specific":[88],"To":[90,162],"end,":[92],"we":[93,168],"build":[94],"an":[95,170],"agentic":[96],"system":[97,124],"which":[99],"research":[101,148],"agent":[102],"iteratively":[103],"designs":[104],"experiments":[105],"refines":[107],"hypotheses.":[108],"When":[109],"evaluated":[110],"against":[111],"expert":[113,137],"explanations":[114,138],"across":[115],"six":[116],"tasks":[119],"literature,":[122],"appears":[125],"competitive.":[126],"However,":[127],"closer":[128],"examination":[129],"reveals":[130,194],"several":[131],"pitfalls":[132],"replication-based":[134,198],"evaluation:":[135],"can":[139],"be":[140],"subjective":[141],"or":[142,159],"incomplete,":[143],"outcome-based":[144],"comparisons":[145],"obscure":[146],"process,":[149],"LLM-based":[151],"may":[153],"reproduce":[154],"published":[155],"findings":[156],"via":[157],"memorization":[158],"informed":[160],"guessing.":[161],"address":[163],"some":[164],"these":[166],"pitfalls,":[167],"propose":[169],"unsupervised":[171],"intrinsic":[172],"based":[174],"on":[175],"functional":[177],"interchangeability":[178],"components.":[181],"Our":[182],"work":[183],"demonstrates":[184],"fundamental":[185],"challenges":[186],"evaluating":[188],"complex":[189],"key":[195],"limitations":[196],"evaluation.":[199]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-24T00:00:00"}