{"id":"https://openalex.org/W4412887907","doi":"https://doi.org/10.18653/v1/2025.findings-acl.1091","title":"Preference Curriculum: LLMs Should Always Be Pretrained on Their Preferred Data","display_name":"Preference Curriculum: LLMs Should Always Be Pretrained on Their Preferred Data","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412887907","doi":"https://doi.org/10.18653/v1/2025.findings-acl.1091"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2025.findings-acl.1091","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.1091","pdf_url":"https://aclanthology.org/2025.findings-acl.1091.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: ACL 2025","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.findings-acl.1091.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Xuemiao Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xuemiao Zhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100307712","display_name":"Liangyu Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu Liangyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091614124","display_name":"Feiyu Duan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Feiyu Duan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102195851","display_name":"Yongwei Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yongwei Zhou","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100631506","display_name":"Sirui Wang","orcid":"https://orcid.org/0000-0001-9519-5741"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sirui Wang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081667345","display_name":"Rongxiang Weng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rongxiang Weng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100695185","display_name":"Jingang Wang","orcid":"https://orcid.org/0000-0002-9988-7187"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jingang Wang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5114353815","display_name":"Xunliang Cai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xunliang Cai","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":7.2088,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.9635514,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"21181","last_page":"21198"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12755","display_name":"Legal Education and Practice Innovations","score":0.955299973487854,"subfield":{"id":"https://openalex.org/subfields/3308","display_name":"Law"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12755","display_name":"Legal Education and Practice Innovations","score":0.955299973487854,"subfield":{"id":"https://openalex.org/subfields/3308","display_name":"Law"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/preference","display_name":"Preference","score":0.7839457988739014},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5178421139717102},{"id":"https://openalex.org/keywords/curriculum","display_name":"Curriculum","score":0.48419955372810364},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34545087814331055},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.269997239112854},{"id":"https://openalex.org/keywords/pedagogy","display_name":"Pedagogy","score":0.11341291666030884},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09950056672096252},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07858723402023315}],"concepts":[{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.7839457988739014},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5178421139717102},{"id":"https://openalex.org/C47177190","wikidata":"https://www.wikidata.org/wiki/Q207137","display_name":"Curriculum","level":2,"score":0.48419955372810364},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34545087814331055},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.269997239112854},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.11341291666030884},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09950056672096252},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07858723402023315}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.findings-acl.1091","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.1091","pdf_url":"https://aclanthology.org/2025.findings-acl.1091.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: ACL 2025","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.findings-acl.1091","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.1091","pdf_url":"https://aclanthology.org/2025.findings-acl.1091.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: ACL 2025","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.5400000214576721,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412887907.pdf","grobid_xml":"https://content.openalex.org/works/W4412887907.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2,97,153],"(LLMs)":[3],"generally":[4],"utilize":[5],"a":[6,81],"consistent":[7],"data":[8,24,35,60,123,204],"distribution":[9,209],"throughout":[10],"the":[11,15,29,44,59,71,76,108,115,122,126,136,139,160,198,207],"pretraining":[12,32],"process.However,":[13],"as":[14,133],"model's":[16,199],"capability":[17],"improves,":[18],"it":[19],"is":[20,83],"intuitive":[21],"that":[22,155],"its":[23],"preferences":[25,182],"dynamically":[26,180],"change,":[27],"indicating":[28],"need":[30],"for":[31,84,95,203],"with":[33,89],"different":[34],"at":[36,128,190],"various":[37],"training":[38,130,145,186,192],"stages.To":[39],"achieve":[40],"it,":[41],"we":[42,69,113],"propose":[43,114],"Perplexity":[45],"Difference":[46],"(PD)":[47],"based":[48],"Preference":[49],"Curriculum":[50],"learning":[51],"(PDPC)":[52],"framework,":[53],"which":[54],"always":[55],"perceives":[56],"and":[57,66,100,120,142,151,177],"uses":[58],"preferred":[61],"by":[62],"LLMs":[63],"to":[64,74,98,104,118,134,179,194,216],"train":[65],"boost":[67],"them.First,":[68],"introduce":[70],"PD":[72,91,196],"metric":[73],"quantify":[75],"difference":[77],"in":[78,107],"how":[79],"challenging":[80,94],"sample":[82],"weak":[85,96],"versus":[86],"strong":[87],"models.Samples":[88],"high":[90],"are":[92,101],"more":[93,102],"learn":[99],"suitable":[103],"be":[105,188],"arranged":[106],"later":[109],"stage":[110],"of":[111,125,138,172],"pretraining.Second,":[112],"preference":[116,124,208],"function":[117],"approximate":[119],"predict":[121],"LLM":[127],"any":[129,191],"step,":[131],"so":[132],"complete":[135],"arrangement":[137],"dataset":[140],"offline":[141],"ensure":[143,217],"continuous":[144],"without":[146,183],"interruption.Experimental":[147],"results":[148],"on":[149,164],"1.3B":[150],"3B":[152,161],"demonstrate":[154],"PDPC":[156],"significantly":[157],"surpasses":[158],"baselines.Notably,":[159],"model":[162],"trained":[163],"1T":[165],"tokens":[166],"achieves":[167],"an":[168],"increased":[169],"average":[170],"accuracy":[171],"over":[173],"8.1%":[174],"across":[175],"MMLU":[176],"CMMLU.How":[178],"perceive":[181],"interrupting":[184],"pretraining.Ideally,":[185],"would":[187],"paused":[189],"step":[193],"calculate":[195],"using":[197],"current":[200],"state,":[201],"allowing":[202],"sampling":[205],"from":[206],"like":[210],"MATES":[211],"(Yu":[212],"et":[213],"al.,":[214],"2024).However,":[215],"con-":[218]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
