{"id":"https://openalex.org/W4401307549","doi":"https://doi.org/10.48550/arxiv.2408.00655","title":"SentenceVAE: Enable Next-sentence Prediction for Large Language Models with Faster Speed, Higher Accuracy and Longer Context","display_name":"SentenceVAE: Enable Next-sentence Prediction for Large Language Models with Faster Speed, Higher Accuracy and Longer Context","publication_year":2024,"publication_date":"2024-08-01","ids":{"openalex":"https://openalex.org/W4401307549","doi":"https://doi.org/10.48550/arxiv.2408.00655"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2408.00655","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2408.00655","pdf_url":"https://arxiv.org/pdf/2408.00655","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2408.00655","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004352156","display_name":"Hongjun An","orcid":"https://orcid.org/0009-0006-3799-7299"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"An, Hongjun","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100405139","display_name":"Yifan Chen","orcid":"https://orcid.org/0000-0002-2776-9456"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Yifan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072771199","display_name":"Zhe Sun","orcid":"https://orcid.org/0000-0002-4224-9811"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Zhe","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100740143","display_name":"Xuelong Li","orcid":"https://orcid.org/0000-0002-0019-4197"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Xuelong","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5004352156"],"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/T10028","display_name":"Topic Modeling","score":0.9977999925613403,"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":0.9977999925613403,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.993399977684021,"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/T13629","display_name":"Text Readability and Simplification","score":0.9175999760627747,"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/inference","display_name":"Inference","score":0.6522340774536133},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6208512783050537},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.55026775598526},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4726896584033966},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46107223629951477}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6522340774536133},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6208512783050537},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.55026775598526},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4726896584033966},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46107223629951477}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2408.00655","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2408.00655","pdf_url":"https://arxiv.org/pdf/2408.00655","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},{"id":"doi:10.48550/arxiv.2408.00655","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2408.00655","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:2408.00655","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2408.00655","pdf_url":"https://arxiv.org/pdf/2408.00655","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},"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/W3204019825"],"abstract_inverted_index":{"Current":[0],"large":[1],"language":[2],"models":[3],"(LLMs)":[4],"primarily":[5],"utilize":[6],"next-token":[7],"prediction":[8],"method":[9,155],"for":[10,135,177],"inference,":[11],"which":[12,44],"significantly":[13,131],"impedes":[14],"their":[15],"processing":[16],"speed.":[17,117],"In":[18,89],"this":[19],"paper,":[20],"we":[21,78],"introduce":[22],"a":[23,46,54,57,61,85],"novel":[24],"inference":[25,34,87,116,158],"methodology":[26],"termed":[27],"next-sentence":[28],"prediction,":[29],"aiming":[30],"at":[31],"enhancing":[32],"the":[33,71,91,98,101,107,140,153,178],"efficiency":[35],"of":[36,76,94,100,142,167],"LLMs.":[37],"We":[38],"present":[39],"Sentence":[40,47,62],"Variational":[41],"Autoencoder":[42],"(SentenceVAE),":[43],"includes":[45],"Encoder":[48],"to":[49,64,120,165,183],"compress":[50],"multiple":[51],"tokens":[52,126],"in":[53],"sentence":[55],"into":[56,70,109],"single":[58],"token,":[59],"and":[60,73,138,171],"Decoder":[63],"reconstruct":[65],"it.":[66],"By":[67],"integrating":[68],"SentenceVAE":[69,92],"input":[72],"output":[74],"layers":[75],"LLMs,":[77,122],"develop":[79],"Sentence-level":[80],"LLMs":[81],"(SLLMs)":[82],"that":[83,152],"employ":[84],"sentence-by-sentence":[86],"method.":[88],"addition,":[90],"module":[93],"SLLMs":[95,123],"can":[96,156],"maintain":[97],"integrity":[99],"original":[102,169],"semantic":[103],"content":[104],"by":[105,160,175],"segmenting":[106],"context":[108,129,180],"sentences,":[110],"thereby":[111],"improving":[112],"accuracy":[113],"while":[114],"boosting":[115],"Moreover,":[118],"compared":[119,182],"previous":[121,184],"process":[124],"fewer":[125],"over":[127],"equivalent":[128,179],"length,":[130,181],"reducing":[132],"memory":[133,173],"demands":[134],"self-attention":[136],"computation":[137],"facilitating":[139],"handling":[141],"longer":[143],"context.":[144],"Extensive":[145],"experiments":[146],"on":[147],"Wanjuan":[148],"dataset":[149],"have":[150],"revealed":[151],"proposed":[154],"accelerate":[157],"speed":[159],"204~365%,":[161],"reduce":[162],"perplexity":[163],"(PPL)":[164],"46~75%":[166],"its":[168],"metric,":[170],"decrease":[172],"overhead":[174],"86~91%":[176],"token-by-token":[185],"methods.":[186]},"counts_by_year":[],"updated_date":"2026-03-25T23:56:10.502304","created_date":"2024-08-04T00:00:00"}
