{"id":"https://openalex.org/W7169801636","doi":"https://doi.org/10.48550/arxiv.2607.16072","title":"Frontier Language Models Struggle to Copy: Text Can Be Better Viewed in 2D","display_name":"Frontier Language Models Struggle to Copy: Text Can Be Better Viewed in 2D","publication_year":2026,"publication_date":"2026-07-17","ids":{"openalex":"https://openalex.org/W7169801636","doi":"https://doi.org/10.48550/arxiv.2607.16072"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.16072","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.16072","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.2607.16072","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102529037","display_name":"Haodong Wen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wen, Haodong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5141194598","display_name":"Yiran Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yiran","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5141209501","display_name":"Yingfa Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Yingfa","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5141169460","display_name":"Kaifeng Lyu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lyu, Kaifeng","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/T10028","display_name":"Topic Modeling","score":0.24779999256134033,"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":0.24779999256134033,"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":0.1386999934911728,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.10980000346899033,"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/copying","display_name":"Copying","score":0.8123999834060669},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.5871000289916992},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.5613999962806702},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5112000107765198},{"id":"https://openalex.org/keywords/spurious-relationship","display_name":"Spurious relationship","score":0.48750001192092896},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.4683000147342682},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.44909998774528503}],"concepts":[{"id":"https://openalex.org/C2779151265","wikidata":"https://www.wikidata.org/wiki/Q1156791","display_name":"Copying","level":2,"score":0.8123999834060669},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7497000098228455},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.5871000289916992},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.5613999962806702},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5112000107765198},{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.48750001192092896},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4765999913215637},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.4683000147342682},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.46470001339912415},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.44909998774528503},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.4377000033855438},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.42289999127388},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.3959999978542328},{"id":"https://openalex.org/C157486923","wikidata":"https://www.wikidata.org/wiki/Q1376436","display_name":"String (physics)","level":2,"score":0.35530000925064087},{"id":"https://openalex.org/C2778571376","wikidata":"https://www.wikidata.org/wiki/Q1355821","display_name":"Frontier","level":2,"score":0.31779998540878296},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.30820000171661377},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3068000078201294}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.16072","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.16072","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.2607.16072","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.16072","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/4","display_name":"Quality Education","score":0.5769026279449463}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"While":[0],"large":[1],"language":[2,157,187],"models":[3,17,158],"(LLMs)":[4],"can":[5,185],"solve":[6],"advanced":[7],"reasoning":[8],"problems":[9],"in":[10,44,164,183],"seconds,":[11],"we":[12,72,190],"show":[13,151],"that":[14,30,152,180],"even":[15],"frontier":[16],"fail":[18],"to":[19,41,117,173,196],"perform":[20],"a":[21,53,79,84,91,95,108],"much":[22],"simpler":[23],"operation:":[24],"exactly":[25],"copying":[26,51,101,129],"an":[27],"input":[28,66,105,131],"string":[29],"lies":[31],"well":[32],"within":[33],"their":[34],"context":[35],"windows.":[36],"We":[37,149],"attribute":[38],"this":[39,70,99,192],"failure":[40],"positional":[42,144,203],"encodings":[43,145],"Transformer":[45],"architectures,":[46],"whose":[47],"inductive":[48],"bias":[49],"favors":[50],"through":[52],"shortcut":[54],"based":[55],"on":[56,159,167],"matching":[57],"local":[58],"contexts":[59],"rather":[60,82],"than":[61,83,137],"carefully":[62],"locating":[63],"the":[64,114,153,199],"corresponding":[65],"positions.":[67],"To":[68],"address":[69],"issue,":[71],"introduce":[73],"2D-RoPE,":[74],"which":[75,112],"organizes":[76],"text":[77,182],"into":[78],"2D":[80,184,202],"grid":[81],"1D":[85],"sequence":[86],"and":[87,94,189],"assigns":[88],"each":[89],"token":[90],"row":[92],"ID":[93],"column":[96,110],"ID.":[97],"Under":[98],"view,":[100],"becomes":[102],"simply":[103],"retrieving":[104],"tokens":[106],"at":[107,130],"fixed":[109],"offset,":[111],"makes":[113],"task":[115],"easy":[116],"learn.":[118],"In":[119],"synthetic":[120],"copy":[121,160],"experiments,":[122],"shallow":[123],"Transformers":[124],"with":[125,169],"2D-RoPE":[126,156],"achieve":[127],"perfect":[128],"lengths":[132],"hundreds":[133],"of":[134,155,201],"times":[135],"longer":[136],"those":[138],"seen":[139],"during":[140],"training,":[141],"whereas":[142],"standard":[143],"fall":[146],"far":[147],"behind.":[148],"further":[150,197],"advantage":[154],"tasks":[161],"consistently":[162],"holds":[163],"large-scale":[165],"pretraining":[166],"DCLM":[168],"model":[170],"sizes":[171],"up":[172],"1.4B":[174],"parameters.":[175],"Overall,":[176],"our":[177],"results":[178],"suggest":[179],"viewing":[181],"benefit":[186],"modeling,":[188],"hope":[191],"encourages":[193],"future":[194],"work":[195],"explore":[198],"potential":[200],"encodings.":[204]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-21T00:00:00"}