{"id":"https://openalex.org/W4399061473","doi":"https://doi.org/10.48550/arxiv.2405.15618","title":"MLPs Learn In-Context on Regression and Classification Tasks","display_name":"MLPs Learn In-Context on Regression and Classification Tasks","publication_year":2024,"publication_date":"2024-05-24","ids":{"openalex":"https://openalex.org/W4399061473","doi":"https://doi.org/10.48550/arxiv.2405.15618"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2405.15618","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2405.15618","pdf_url":"https://arxiv.org/pdf/2405.15618","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2405.15618","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5080017321","display_name":"William L. Tong","orcid":"https://orcid.org/0000-0003-4319-4303"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tong, William L.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5023195984","display_name":"Cengiz Pehlevan","orcid":"https://orcid.org/0000-0001-9767-6063"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pehlevan, Cengiz","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":2,"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":0.3813000023365021,"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":0.3813000023365021,"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/T10656","display_name":"Child and Animal Learning Development","score":0.1137000024318695,"subfield":{"id":"https://openalex.org/subfields/3204","display_name":"Developmental and Educational Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.08510000258684158,"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/context","display_name":"Context (archaeology)","score":0.6017638444900513},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4517081677913666},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3491750657558441},{"id":"https://openalex.org/keywords/history","display_name":"History","score":0.12387353181838989},{"id":"https://openalex.org/keywords/archaeology","display_name":"Archaeology","score":0.03986957669258118}],"concepts":[{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6017638444900513},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4517081677913666},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3491750657558441},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.12387353181838989},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.03986957669258118}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2405.15618","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2405.15618","pdf_url":"https://arxiv.org/pdf/2405.15618","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2405.15618","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2405.15618","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":"pmh:oai:arXiv.org:2405.15618","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2405.15618","pdf_url":"https://arxiv.org/pdf/2405.15618","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W2382290278","https://openalex.org/W4395014643"],"abstract_inverted_index":{"In-context":[0],"learning":[1,98],"(ICL),":[2],"the":[3,45,56,118,129,172],"remarkable":[4],"ability":[5,109],"to":[6,17,79,87,110,135,169],"solve":[7,111],"a":[8,19,71,93,124,153],"task":[9],"from":[10,76],"only":[11],"input":[12],"exemplars,":[13],"is":[14],"often":[15],"assumed":[16],"be":[18],"unique":[20],"hallmark":[21],"of":[22,73,121,162,176],"Transformer":[23,136],"models.":[24],"By":[25],"examining":[26],"commonly":[27],"employed":[28],"synthetic":[29,125],"ICL":[30],"tasks,":[31,150],"we":[32],"demonstrate":[33],"that":[34,66],"multi-layer":[35],"perceptrons":[36],"(MLPs)":[37],"can":[38],"also":[39,103],"learn":[40,50],"in-context.":[41],"Moreover,":[42],"MLPs,":[43],"and":[44,127,151],"closely":[46,85],"related":[47,86],"MLP-Mixer":[48],"models,":[49],"in-context":[51,88,97],"comparably":[52],"with":[53],"Transformers":[54,69,145],"under":[55],"same":[57],"compute":[58],"budget":[59],"in":[60,123,132,165],"this":[61],"setting.":[62],"We":[63,158],"further":[64,160],"show":[65],"MLPs":[67,122,142],"outperform":[68],"on":[70,148],"series":[72],"classical":[74],"tasks":[75],"psychology":[77],"designed":[78],"test":[80],"relational":[81,112],"reasoning,":[82],"which":[83],"are":[84],"classification.":[89],"These":[90],"results":[91,116],"underscore":[92],"need":[94],"for":[95],"studying":[96],"beyond":[99],"attention-based":[100,177],"architectures,":[101],"while":[102],"challenging":[104],"prior":[105],"arguments":[106],"against":[107,144],"MLPs'":[108],"tasks.":[113],"Altogether,":[114],"our":[115],"highlight":[117],"unexpected":[119],"competence":[120],"setting,":[126],"support":[128],"growing":[130],"interest":[131],"all-MLP":[133],"alternatives":[134],"architectures.":[137],"It":[138],"remains":[139],"unclear":[140],"how":[141],"perform":[143],"at":[146],"scale":[147],"real-world":[149],"where":[152],"performance":[154],"gap":[155],"may":[156],"originate.":[157],"encourage":[159],"exploration":[161],"these":[163],"architectures":[164],"more":[166],"complex":[167],"settings":[168],"better":[170],"understand":[171],"potential":[173],"comparative":[174],"advantage":[175],"schemes.":[178]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-08-05T07:39:15.569665","created_date":"2024-05-28T00:00:00"}
