{"id":"https://openalex.org/W4396821494","doi":"https://doi.org/10.48550/arxiv.2404.19737","title":"Better &amp; Faster Large Language Models via Multi-token Prediction","display_name":"Better &amp; Faster Large Language Models via Multi-token Prediction","publication_year":2024,"publication_date":"2024-04-30","ids":{"openalex":"https://openalex.org/W4396821494","doi":"https://doi.org/10.48550/arxiv.2404.19737"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2404.19737","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2404.19737","pdf_url":"https://arxiv.org/pdf/2404.19737","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/2404.19737","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5092698871","display_name":"Fabian Gloeckle","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gloeckle, Fabian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068866092","display_name":"Badr Youbi Idrissi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Idrissi, Badr Youbi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048065823","display_name":"Baptiste Rozi\u00e8re","orcid":"https://orcid.org/0000-0002-9014-4379"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rozi\u00e8re, Baptiste","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087642472","display_name":"David L\u00f3pez-Paz","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lopez-Paz, David","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5041907084","display_name":"Gabriel Synnaeve","orcid":"https://orcid.org/0000-0003-1715-3356"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Synnaeve, Gabriel","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":true,"cited_by_count":9,"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":0.9918000102043152,"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":0.9918000102043152,"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":0.9764999747276306,"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/computer-science","display_name":"Computer science","score":0.6987854838371277},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.6785784959793091},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.43793123960494995},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3525032103061676},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.33134347200393677},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.15757206082344055}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6987854838371277},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.6785784959793091},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.43793123960494995},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3525032103061676},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.33134347200393677},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.15757206082344055}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2404.19737","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2404.19737","pdf_url":"https://arxiv.org/pdf/2404.19737","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.2404.19737","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2404.19737","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:2404.19737","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2404.19737","pdf_url":"https://arxiv.org/pdf/2404.19737","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":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4396821494.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W4388335561","https://openalex.org/W2970530566","https://openalex.org/W4288261899","https://openalex.org/W4307309205","https://openalex.org/W2967478618","https://openalex.org/W4385009901","https://openalex.org/W4385572700","https://openalex.org/W3204019825"],"abstract_inverted_index":{"Large":[0],"language":[1,22,92],"models":[2,23,123,135,178],"such":[3],"as":[4,71],"GPT":[5],"and":[6,90,103,143,170],"Llama":[7],"are":[8,113,183],"trained":[9,179],"with":[10,81,180,192],"a":[11,64],"next-token":[12,151],"prediction":[13,70,161,182],"loss.":[14],"In":[15],"this":[16],"work,":[17],"we":[18,45,76],"suggest":[19],"that":[20,159],"training":[21,43,74,85,108],"to":[24,49,185],"predict":[25,50],"multiple":[26,110],"future":[27],"tokens":[28,54],"at":[29,38,189],"once":[30],"results":[31],"in":[32,41,84],"higher":[33],"sample":[34],"efficiency.":[35],"More":[36],"specifically,":[37],"each":[39],"position":[40],"the":[42,47,51,165],"corpus,":[44],"ask":[46],"model":[48,66,101],"following":[52],"n":[53,56],"using":[55],"independent":[57],"output":[58],"heads,":[59],"operating":[60],"on":[61,116,141,147,154],"top":[62],"of":[63,167],"shared":[65],"trunk.":[67],"Considering":[68],"multi-token":[69,160],"an":[72,175],"auxiliary":[73],"task,":[75],"measure":[77],"improved":[78],"downstream":[79],"capabilities":[80],"no":[82],"overhead":[83],"time":[86],"for":[87,99,109,164],"both":[88],"code":[89],"natural":[91],"models.":[93,152],"The":[94],"method":[95],"is":[96,162],"increasingly":[97],"useful":[98],"larger":[100],"sizes,":[102],"keeps":[104],"its":[105],"appeal":[106],"when":[107],"epochs.":[111],"Gains":[112],"especially":[114],"pronounced":[115],"generative":[117],"benchmarks":[118],"like":[119],"coding,":[120],"where":[121],"our":[122],"consistently":[124],"outperform":[125],"strong":[126],"baselines":[127],"by":[128],"several":[129],"percentage":[130],"points.":[131],"Our":[132],"13B":[133],"parameter":[134],"solves":[136],"12":[137],"%":[138,145],"more":[139,146],"problems":[140],"HumanEval":[142],"17":[144],"MBPP":[148],"than":[149],"comparable":[150],"Experiments":[153],"small":[155],"algorithmic":[156,171],"tasks":[157],"demonstrate":[158],"favorable":[163],"development":[166],"induction":[168],"heads":[169],"reasoning":[172],"capabilities.":[173],"As":[174],"additional":[176],"benefit,":[177],"4-token":[181],"up":[184],"3":[186],"times":[187],"faster":[188],"inference,":[190],"even":[191],"large":[193],"batch":[194],"sizes.":[195]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3}],"updated_date":"2026-08-11T07:18:39.950985","created_date":"2024-05-11T00:00:00"}
