{"id":"https://openalex.org/W7151631082","doi":"https://doi.org/10.48550/arxiv.2604.04756","title":"Darkness Visible: Reading the Exception Handler of a Language Model","display_name":"Darkness Visible: Reading the Exception Handler of a Language Model","publication_year":2026,"publication_date":"2026-04-06","ids":{"openalex":"https://openalex.org/W7151631082","doi":"https://doi.org/10.48550/arxiv.2604.04756"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.04756","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.04756","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.2604.04756","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133091925","display_name":"Peter Balogh","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Balogh, Peter","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5133091925"],"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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.4140999913215637,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.4140999913215637,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","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"}},{"id":"https://openalex.org/T10465","display_name":"Neurobiology of Language and Bilingualism","score":0.05810000002384186,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/vocabulary","display_name":"Vocabulary","score":0.5885000228881836},{"id":"https://openalex.org/keywords/reading","display_name":"Reading (process)","score":0.5752000212669373},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.557200014591217},{"id":"https://openalex.org/keywords/crossover","display_name":"Crossover","score":0.49950000643730164},{"id":"https://openalex.org/keywords/reset","display_name":"Reset (finance)","score":0.49639999866485596},{"id":"https://openalex.org/keywords/routing","display_name":"Routing (electronic design automation)","score":0.47769999504089355},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4767000079154968},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.44780001044273376},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4406000077724457}],"concepts":[{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.5885000228881836},{"id":"https://openalex.org/C554936623","wikidata":"https://www.wikidata.org/wiki/Q199657","display_name":"Reading (process)","level":2,"score":0.5752000212669373},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.557200014591217},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.510200023651123},{"id":"https://openalex.org/C122507166","wikidata":"https://www.wikidata.org/wiki/Q628906","display_name":"Crossover","level":2,"score":0.49950000643730164},{"id":"https://openalex.org/C2779795794","wikidata":"https://www.wikidata.org/wiki/Q7315343","display_name":"Reset (finance)","level":2,"score":0.49639999866485596},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.47769999504089355},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4767000079154968},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.46950000524520874},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.44780001044273376},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4406000077724457},{"id":"https://openalex.org/C60048249","wikidata":"https://www.wikidata.org/wiki/Q37437","display_name":"Syntax","level":2,"score":0.37389999628067017},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3662000000476837},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.36410000920295715},{"id":"https://openalex.org/C197640229","wikidata":"https://www.wikidata.org/wiki/Q2534066","display_name":"Predictability","level":2,"score":0.3610999882221222},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.3418000042438507},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.3237999975681305},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.320499986410141},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.31310001015663147},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.30880001187324524},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.30790001153945923},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3068999946117401},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.29789999127388},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.296099990606308},{"id":"https://openalex.org/C98184364","wikidata":"https://www.wikidata.org/wiki/Q1780131","display_name":"Argument (complex analysis)","level":2,"score":0.28700000047683716},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.28189998865127563},{"id":"https://openalex.org/C2778121359","wikidata":"https://www.wikidata.org/wiki/Q8096","display_name":"Lexicon","level":2,"score":0.2775999903678894},{"id":"https://openalex.org/C126706616","wikidata":"https://www.wikidata.org/wiki/Q2944660","display_name":"Lexical item","level":2,"score":0.27059999108314514},{"id":"https://openalex.org/C2776141515","wikidata":"https://www.wikidata.org/wiki/Q1274479","display_name":"Repetition (rhetorical device)","level":2,"score":0.26249998807907104}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.04756","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.04756","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.2604.04756","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.04756","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":[{"id":"https://metadata.un.org/sdg/9","score":0.4141760468482971,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,76],"final":[1,192],"MLP":[2,81,130],"of":[3,118],"GPT-2":[4,156],"Small":[5],"exhibits":[6],"a":[7,18,72,151],"fully":[8],"legible":[9],"routing":[10,123],"program":[11],"--":[12,22,79,88,155,182],"27":[13],"named":[14],"neurons":[15,38,46,68],"organized":[16],"into":[17],"three-tier":[19],"exception":[20,164],"handler":[21,165],"while":[23],"the":[24,129,138,163,179,191],"knowledge":[25],"it":[26],"routes":[27],"remains":[28],"entangled":[29],"across":[30],"~3,040":[31],"residual":[32,139],"neurons.":[33],"We":[34],"decompose":[35],"all":[36,98],"3,072":[37],"(to":[39],"numerical":[40],"precision)":[41],"into:":[42],"5":[43,59],"fused":[44],"Core":[45],"that":[47,55,61,69,109],"reset":[48],"vocabulary":[49],"toward":[50],"function":[51,121],"words,":[52],"10":[53],"Differentiators":[54],"suppress":[56],"wrong":[57],"candidates,":[58],"Specialists":[60],"detect":[62],"structural":[63],"boundaries,":[64],"and":[65,104,199],"7":[66],"Consensus":[67],"each":[70],"monitor":[71],"distinct":[73],"linguistic":[74],"dimension.":[75],"consensus-exception":[77],"crossover":[78,101],"where":[80],"intervention":[82],"shifts":[83],"from":[84,141],"helpful":[85],"to":[86],"harmful":[87],"is":[89],"statistically":[90],"sharp":[91],"(bootstrap":[92],"95%":[93],"CIs":[94],"exclude":[95],"zero":[96],"at":[97,116,167,178,190,195],"consensus":[99],"levels;":[100],"between":[102],"4/7":[103],"5/7).":[105],"Three":[106],"experiments":[107],"show":[108],"\"knowledge":[110],"neurons\"":[111],"(Dai":[112],"et":[113],"al.,":[114],"2022),":[115],"L11":[117],"this":[119],"model,":[120],"as":[122],"infrastructure":[124],"rather":[125,170],"than":[126,171],"fact":[127],"storage:":[128],"amplifies":[131],"or":[132],"suppresses":[133],"signals":[134],"already":[135],"present":[136],"in":[137,183],"stream":[140],"attention,":[142],"scaling":[143],"with":[144,162],"contextual":[145],"constraint.":[146],"A":[147],"garden-path":[148,153],"experiment":[149],"reveals":[150],"reversed":[152],"effect":[154],"uses":[157],"verb":[158],"subcategorization":[159],"immediately,":[160],"consistent":[161],"operating":[166],"token-level":[168],"predictability":[169],"syntactic":[172],"structure.":[173],"This":[174],"architecture":[175],"crystallizes":[176],"only":[177],"terminal":[180],"layer":[181,196],"deeper":[184],"models,":[185],"we":[186],"predict":[187],"equivalent":[188],"structure":[189],"layer,":[193],"not":[194],"11.":[197],"Code":[198],"data:":[200],"https://github.com/pbalogh/transparent-gpt2":[201]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-04-08T00:00:00"}
