{"id":"https://openalex.org/W4416522900","doi":"https://doi.org/10.48550/arxiv.2506.23875","title":"Discovering Learning-Friendly Generation Orders for Sequential Computation","display_name":"Discovering Learning-Friendly Generation Orders for Sequential Computation","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416522900","doi":"https://doi.org/10.48550/arxiv.2506.23875"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2506.23875","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.23875","pdf_url":"https://arxiv.org/pdf/2506.23875","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"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/2506.23875","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023377803","display_name":"Yuta Sato","orcid":"https://orcid.org/0000-0001-7871-5733"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sato, Yuta","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010514962","display_name":"Kazuhiko Kawamoto","orcid":"https://orcid.org/0000-0003-3701-1961"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kawamoto, Kazuhiko","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5055384327","display_name":"Hiroshi Kera","orcid":"https://orcid.org/0000-0002-9830-0436"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kera, Hiroshi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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/T11345","display_name":"Cognitive and developmental aspects of mathematical skills","score":0.7651000022888184,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11345","display_name":"Cognitive and developmental aspects of mathematical skills","score":0.7651000022888184,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.049400001764297485,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11574","display_name":"Artificial Intelligence in Games","score":0.019200000911951065,"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/sequence","display_name":"Sequence (biology)","score":0.52920001745224},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.4925000071525574},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4772999882698059},{"id":"https://openalex.org/keywords/multiplication","display_name":"Multiplication (music)","score":0.44780001044273376},{"id":"https://openalex.org/keywords/chain","display_name":"Chain (unit)","score":0.40560001134872437},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.38940000534057617}],"concepts":[{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.7432000041007996},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6074000000953674},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.52920001745224},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.4925000071525574},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4772999882698059},{"id":"https://openalex.org/C2780595030","wikidata":"https://www.wikidata.org/wiki/Q3860309","display_name":"Multiplication (music)","level":2,"score":0.44780001044273376},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4372999966144562},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42899999022483826},{"id":"https://openalex.org/C199185054","wikidata":"https://www.wikidata.org/wiki/Q552299","display_name":"Chain (unit)","level":2,"score":0.40560001134872437},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.38940000534057617},{"id":"https://openalex.org/C204160518","wikidata":"https://www.wikidata.org/wiki/Q122653","display_name":"Numeral system","level":2,"score":0.33889999985694885},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33799999952316284},{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.30399999022483826},{"id":"https://openalex.org/C40506919","wikidata":"https://www.wikidata.org/wiki/Q7452469","display_name":"Sequence learning","level":2,"score":0.2939000129699707},{"id":"https://openalex.org/C182775192","wikidata":"https://www.wikidata.org/wiki/Q913725","display_name":"Saturation arithmetic","level":3,"score":0.27059999108314514},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2556999921798706},{"id":"https://openalex.org/C2994113290","wikidata":"https://www.wikidata.org/wiki/Q7452469","display_name":"Serial learning","level":3,"score":0.2533000111579895}],"mesh":[],"locations_count":4,"locations":[{"id":"pmh:oai:arXiv.org:2506.23875","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.23875","pdf_url":"https://arxiv.org/pdf/2506.23875","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:arXiv.org:2506.23875","is_oa":true,"landing_page_url":"https://arxiv.org/abs/2506.23875","pdf_url":"https://arxiv.org/pdf/2506.23875","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:doi:10.48550/arxiv.2506.23875","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2506.23875","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2506.23875","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2506.23875","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.23875","pdf_url":"https://arxiv.org/pdf/2506.23875","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1478072996","display_name":null,"funder_award_id":"JPJS00420230002","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"},{"id":"https://openalex.org/F4320338111","display_name":"Precursory Research for Embryonic Science and Technology","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Sequential":[0],"computation":[1],"via":[2],"autoregressive":[3],"generation":[4,12],"can":[5],"make":[6],"difficult":[7],"tasks":[8],"learnable,":[9],"but":[10],"the":[11,24,52,68,78,102,134,166,176],"order":[13,31,136],"of":[14,26,55,71,154,165],"intermediate":[15],"states":[16],"strongly":[17],"affects":[18],"whether":[19],"training":[20],"succeeds.":[21],"We":[22,57],"address":[23],"problem":[25],"discovering":[27],"a":[28,47,72,87,151,172],"learning-friendly":[29,44,173],"target":[30],"automatically,":[32],"rather":[33],"than":[34],"relying":[35],"on":[36],"task-specific":[37],"design.":[38],"Our":[39],"key":[40],"observation":[41],"is":[42],"that":[43,137],"orders":[45,66,106,181],"cause":[46],"faster":[48],"loss":[49,70,84,169],"drop":[50],"in":[51,86,143],"early":[53],"stage":[54],"training.":[56],"exploit":[58],"this":[59],"by":[60,67],"\\emph{loss":[61],"profiling},":[62],"which":[63],"ranks":[64],"candidate":[65,80],"early-stage":[69],"single":[73],"short":[74],"run.":[75],"To":[76],"handle":[77],"factorial":[79],"space,":[81],"we":[82],"wrap":[83],"profiling":[85,170],"hierarchical":[88],"global":[89,177],"--":[90],"local":[91],"search":[92,178],"over":[93],"block-":[94],"and":[95,113,175],"within-block-level":[96],"orderings.":[97],"On":[98,129,146],"six":[99],"order-sensitive":[100],"tasks,":[101],"method":[103],"discovers":[104,180],"effective":[105],"up":[107,114],"to":[108,115,126,140],"$L=13$":[109],"from":[110,117,123],"random":[111],"initialization":[112],"$L=40$":[116],"structured":[118],"initialization,":[119],"lifting":[120],"success":[121],"rates":[122],"about":[124],"10\\%":[125],"near":[127],"100\\%.":[128],"integer":[130],"multiplication,":[131],"it":[132],"rediscovers":[133],"reverse-digit":[135],"was":[138],"reported":[139],"be":[141],"efficient":[142],"prior":[144],"studies.":[145],"delay":[147],"dynamical":[148],"systems,":[149],"as":[150],"case":[152],"study":[153],"multi-variate":[155],"recurrences,":[156],"learnability":[157],"varies":[158],"sharply":[159],"even":[160,179],"among":[161],"valid":[162],"topological":[163],"sorts":[164],"dependency":[167],"graph:":[168],"identifies":[171],"one,":[174],"surpassing":[182],"hand-designed":[183],"candidates.":[184]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
