{"id":"https://openalex.org/W7162687488","doi":"https://doi.org/10.48550/arxiv.2605.28328","title":"Learning the Error Patterns of Language Models","display_name":"Learning the Error Patterns of Language Models","publication_year":2026,"publication_date":"2026-05-27","ids":{"openalex":"https://openalex.org/W7162687488","doi":"https://doi.org/10.48550/arxiv.2605.28328"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.28328","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.28328","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.28328","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137230926","display_name":"Jinwoo Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Jinwoo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137251744","display_name":"Taylor Berg-KirkPatrick","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Berg-KirkPatrick, Taylor","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5089920000","display_name":"Loris D\u2019Antoni","orcid":"https://orcid.org/0000-0001-9625-4037"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"D'Antoni, Loris","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/T10181","display_name":"Natural Language Processing Techniques","score":0.4690000116825104,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.4690000116825104,"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/T10028","display_name":"Topic Modeling","score":0.14159999787807465,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.09830000251531601,"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/prefix","display_name":"Prefix","score":0.5824000239372253},{"id":"https://openalex.org/keywords/python","display_name":"Python (programming language)","score":0.45570001006126404},{"id":"https://openalex.org/keywords/typescript","display_name":"TypeScript","score":0.4059000015258789},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.34529998898506165},{"id":"https://openalex.org/keywords/trie","display_name":"Trie","score":0.3449999988079071},{"id":"https://openalex.org/keywords/compiler","display_name":"Compiler","score":0.3208000063896179}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6721000075340271},{"id":"https://openalex.org/C141603448","wikidata":"https://www.wikidata.org/wiki/Q134830","display_name":"Prefix","level":2,"score":0.5824000239372253},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.45570001006126404},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4108999967575073},{"id":"https://openalex.org/C2777869424","wikidata":"https://www.wikidata.org/wiki/Q978185","display_name":"TypeScript","level":2,"score":0.4059000015258789},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35670000314712524},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.35519999265670776},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.34529998898506165},{"id":"https://openalex.org/C190290938","wikidata":"https://www.wikidata.org/wiki/Q387015","display_name":"Trie","level":3,"score":0.3449999988079071},{"id":"https://openalex.org/C169590947","wikidata":"https://www.wikidata.org/wiki/Q47506","display_name":"Compiler","level":2,"score":0.3208000063896179},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.3018999993801117},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2939999997615814},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.29100000858306885},{"id":"https://openalex.org/C103088060","wikidata":"https://www.wikidata.org/wiki/Q1062839","display_name":"Error detection and correction","level":2,"score":0.2874999940395355},{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.2791000008583069},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.26579999923706055},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2526000142097473}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.28328","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.28328","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.28328","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.28328","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":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"When":[0],"generating":[1,32],"outputs":[2,108],"for":[3,24,122],"domains":[4],"with":[5],"specific":[6],"validity":[7],"constraints":[8,48],"(e.g.,":[9],"a":[10,18,44,110],"program":[11],"should":[12],"compile),":[13],"LLMs":[14],"often":[15],"fail":[16],"in":[17,53,80],"small":[19,45],"number":[20,46],"of":[21,47,98,109],"focused":[22],"ways:":[23],"example,":[25,117],"by":[26,88,127],"using":[27,43],"Python":[28],"function":[29],"names":[30],"when":[31],"TypeScript.":[33],"We":[34,55],"observe":[35],"that":[36,49],"these":[37],"error":[38,69,96],"patterns":[39,97],"can":[40,50,102],"be":[41,51,103],"represented":[42],"learned":[52,87],"practice.":[54],"propose":[56],"\\emph{prefix":[57],"filters},":[58],"which":[59],"are":[60],"per-domain-and-LLM":[61],"symbolic":[62],"functions,":[63],"as":[64,72],"objects":[65],"to":[66,75,105,132,136],"capture":[67],"the":[68,95,107],"patterns,":[70],"Palla":[71,89,118],"an":[73],"algorithm":[74],"learn":[76],"prefix":[77],"filters":[78,86],"efficiently":[79],"practice,":[81],"and":[82,100],"implement":[83],"Palla.":[84],"Prefix":[85],"i)":[90],"help":[91],"us":[92],"quantitatively":[93],"analyze":[94],"LLMs,":[99],"ii)":[101],"used":[104],"constrain":[106],"model":[111],"via":[112],"constrained":[113],"sampling":[114],"algorithms.":[115],"For":[116],"boosts":[119],"compile":[120],"rates":[121],"Qwen2.5-1.5B":[123,131],"on":[124],"TypeScript":[125],"generation,":[126],"over":[128],"60%,":[129],"allowing":[130],"achieve":[133],"similar":[134],"performance":[135],"Llama3.1-8B":[137],"unconstrained.":[138]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-29T00:00:00"}