{"id":"https://openalex.org/W7162683173","doi":"https://doi.org/10.48550/arxiv.2605.27390","title":"EvoSpec: Evolving Speculative Decoding via Real-Time Vocabulary and Parameter Adaptation","display_name":"EvoSpec: Evolving Speculative Decoding via Real-Time Vocabulary and Parameter Adaptation","publication_year":2026,"publication_date":"2026-04-17","ids":{"openalex":"https://openalex.org/W7162683173","doi":"https://doi.org/10.48550/arxiv.2605.27390"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.27390","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.27390","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":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.27390","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137266675","display_name":"Shuyu Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Shuyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102532142","display_name":"Lingfeng Pan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pan, Lingfeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137283058","display_name":"Qicheng Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Qicheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017271787","display_name":"Yaqi Shi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shi, Yaqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137240235","display_name":"Yueyang Tan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tan, Yueyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007574334","display_name":"Ruyu Yan","orcid":"https://orcid.org/0000-0003-4037-8342"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yan, Ruyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137252974","display_name":"Jiaqi Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Jiaqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064444822","display_name":"\u675c\u7acb\u884c","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Du, Lixing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137244868","display_name":"Lu Wang","orcid":"https://orcid.org/0009-0009-0993-4719"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Lu","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":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/T13910","display_name":"Computational and Text Analysis Methods","score":0.2784999907016754,"subfield":{"id":"https://openalex.org/subfields/3300","display_name":"General Social Sciences"},"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/T13910","display_name":"Computational and Text Analysis Methods","score":0.2784999907016754,"subfield":{"id":"https://openalex.org/subfields/3300","display_name":"General Social Sciences"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.2214999943971634,"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":0.09019999951124191,"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/bottleneck","display_name":"Bottleneck","score":0.6122000217437744},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5947999954223633},{"id":"https://openalex.org/keywords/vocabulary","display_name":"Vocabulary","score":0.5946000218391418},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.5604000091552734},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.5454000234603882},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5169000029563904},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.5131000280380249},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.48159998655319214},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.38359999656677246}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8528000116348267},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.6122000217437744},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5947999954223633},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.5946000218391418},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.5604000091552734},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.5454000234603882},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5169000029563904},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.5131000280380249},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49639999866485596},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.48159998655319214},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.38359999656677246},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.366100013256073},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.359499990940094},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.35010001063346863},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.3472999930381775},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3409999907016754},{"id":"https://openalex.org/C206134035","wikidata":"https://www.wikidata.org/wiki/Q811525","display_name":"Treebank","level":3,"score":0.33070001006126404},{"id":"https://openalex.org/C204806902","wikidata":"https://www.wikidata.org/wiki/Q2333581","display_name":"Semantic security","level":5,"score":0.31949999928474426},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.29600000381469727},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.2827000021934509},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.27950000762939453},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.27129998803138733},{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.27070000767707825},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.267300009727478},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.26330000162124634},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2628999948501587},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.25859999656677246},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.25540000200271606}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.27390","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.27390","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.27390","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.27390","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":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.6147710084915161,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Speculative":[0],"decoding":[1,138],"accelerates":[2],"Large":[3],"Language":[4],"Model":[5],"inference":[6],"through":[7],"draft-then-verify":[8],"generation,":[9],"yet":[10],"lightweight":[11,104],"draft":[12,27,65,70,83,105],"models":[13],"face":[14],"coupled":[15],"efficiency":[16],"and":[17,29,61,91,103,114,118,139,149],"quality":[18],"limitations:":[19],"large-vocabulary":[20],"output":[21],"projection":[22,42],"is":[23,78],"costly,":[24],"while":[25,52,124,145],"limited":[26,64],"capacity":[28,66],"static":[30,45],"parameters":[31,106],"reduce":[32],"acceptance":[33],"under":[34],"specialized":[35],"or":[36],"shifting":[37],"inputs.":[38],"Vocabulary":[39],"pruning":[40],"lowers":[41],"cost,":[43],"but":[44,85],"variants":[46,54],"miss":[47],"locally":[48],"important":[49],"long-tail":[50],"tokens,":[51],"dynamic":[53],"remain":[55],"sensitive":[56],"to":[57],"preset":[58],"selection":[59],"policies":[60],"budgets.":[62],"Moreover,":[63],"can":[67],"leave":[68],"the":[69,75,100],"distribution":[71],"misaligned":[72],"even":[73],"when":[74],"target":[76],"token":[77,116],"covered.":[79],"Online":[80],"alignment":[81,123],"improves":[82],"quality,":[84],"full-parameter":[86,158],"updates":[87],"introduce":[88,95],"substantial":[89],"memory":[90,156],"latency":[92],"overhead.":[93],"We":[94],"EvoSpec,":[96],"which":[97],"jointly":[98],"adapts":[99],"active":[101],"vocabulary":[102],"from":[107],"verification":[108],"feedback.":[109],"EvoSpec":[110,131],"asynchronously":[111],"retrieves":[112],"semantic":[113],"statistical":[115],"neighbors":[117],"performs":[119],"curriculum-weighted":[120],"online":[121,159],"LoRA":[122],"preserving":[125],"exact":[126],"target-model":[127],"verification.":[128],"On":[129],"Qwen3-8B/EAGLE-2,":[130],"reaches":[132],"a":[133,140],"$2.18\\times$":[134],"speedup":[135],"over":[136,143],"vanilla":[137],"$1.20\\times$":[141],"gain":[142],"EAGLE-2,":[144],"improving":[146],"specialized-domain":[147],"coverage":[148],"using":[150],"$27\\%$":[151],"less":[152],"auxiliary":[153],"GPU":[154],"adaptation":[155],"than":[157],"adaptation.":[160]},"counts_by_year":[],"updated_date":"2026-07-25T05:54:39.514286","created_date":"2026-05-29T00:00:00"}
