{"id":"https://openalex.org/W7129124592","doi":"https://doi.org/10.48550/arxiv.2602.12957","title":"HSD: Training-Free Acceleration for Document Parsing Vision-Language Model with Hierarchical Speculative Decoding","display_name":"HSD: Training-Free Acceleration for Document Parsing Vision-Language Model with Hierarchical Speculative Decoding","publication_year":2026,"publication_date":"2026-02-13","ids":{"openalex":"https://openalex.org/W7129124592","doi":"https://doi.org/10.48550/arxiv.2602.12957"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.12957","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5079914128","display_name":"Wenhui Liao","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Liao, Wenhui","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126125219","display_name":"Hongliang Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Hongliang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126134293","display_name":"Pengyu Xie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Pengyu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126108048","display_name":"Xinyu Cai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cai, Xinyu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126110596","display_name":"Yufan Shen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shen, Yufan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126073325","display_name":"Yi Xin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xin, Yi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126133011","display_name":"Qi Qin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qin, Qi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114653165","display_name":"Shenglong Ye","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ye, Shenglong","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107640963","display_name":"Tianbin Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Tianbin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126127868","display_name":"Ming Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Ming","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126102520","display_name":"Junjun He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Junjun","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126169816","display_name":"Yihao Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yihao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126152834","display_name":"Wenhai Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Wenhai","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116004336","display_name":"Min Dou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dou, Min","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126164022","display_name":"Bin Fu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fu, Bin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Shi, Botian","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shi, Botian","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126082967","display_name":"Yu Qiao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qiao, Yu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5126148875","display_name":"Lianwen Jin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jin, Lianwen","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":18,"corresponding_author_ids":["https://openalex.org/A5079914128"],"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/T10181","display_name":"Natural Language Processing Techniques","score":0.6751000285148621,"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":0.6751000285148621,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.08479999750852585,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.04500000178813934,"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/parsing","display_name":"Parsing","score":0.7827000021934509},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6988000273704529},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.545199990272522},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5252000093460083},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.48100000619888306},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.47110000252723694},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.45910000801086426}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8666999936103821},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.7827000021934509},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6988000273704529},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.545199990272522},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5252000093460083},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.48100000619888306},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.47110000252723694},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4603999853134155},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.45910000801086426},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.43619999289512634},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.39149999618530273},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.3434000015258789},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.31790000200271606},{"id":"https://openalex.org/C81081738","wikidata":"https://www.wikidata.org/wiki/Q55542","display_name":"Lossless compression","level":3,"score":0.3127000033855438},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3111000061035156},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.2897000014781952},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2879999876022339},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.25850000977516174},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2556000053882599}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.12957","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2602.12957","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.12957","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:doi:10.48550/arxiv.2602.12957","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.8206878900527954,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Document":[0],"parsing":[1,175],"is":[2],"a":[3,10,99,109,159],"fundamental":[4],"task":[5],"in":[6,41,132],"multimodal":[7],"understanding,":[8],"supporting":[9],"wide":[11],"range":[12],"of":[13,180],"downstream":[14],"applications":[15],"such":[16],"as":[17,37,53],"information":[18],"extraction":[19],"and":[20,29,84,117,168],"intelligent":[21],"document":[22,104],"analysis.":[23],"Benefiting":[24],"from":[25,49],"strong":[26],"semantic":[27],"modeling":[28],"robust":[30],"generalization,":[31],"VLM-based":[32],"end-to-end":[33],"approaches":[34],"have":[35],"emerged":[36],"the":[38,128,137,178],"mainstream":[39],"paradigm":[40],"recent":[42,66],"years.":[43],"However,":[44],"these":[45,145],"models":[46],"often":[47],"suffer":[48],"substantial":[50],"inference":[51],"latency,":[52],"they":[54],"must":[55],"autoregressively":[56],"generate":[57,118],"long,":[58],"full-page":[59,82,150],"sequences":[60],"when":[61],"processing":[62],"long-form":[63],"documents.":[64],"While":[65],"hybrid":[67],"methods":[68],"mitigate":[69],"this":[70,91],"issue":[71],"via":[72],"region-level":[73,130],"parallel":[74,133],"decoding":[75,80],"with":[76,163],"VLMs,":[77],"independent":[78],"region":[79,115],"loses":[81],"context":[83],"might":[85],"weaken":[86],"global":[87],"coherence.":[88,151],"To":[89],"address":[90],"issue,":[92],"we":[93],"propose":[94],"Hierarchical":[95],"Speculative":[96],"Decoding":[97],"(HSD),":[98],"two-stage":[100],"local-to-global":[101],"framework":[102],"for":[103,121,134],"parsing.":[105],"HSD":[106,157],"first":[107,125],"employs":[108],"lightweight":[110],"pipeline":[111],"drafter":[112],"to":[113,148,170,189],"predict":[114],"partitions":[116],"coarse":[119],"drafts":[120,131],"each":[122],"region.":[123],"The":[124],"stage":[126,139],"verifies":[127],"generated":[129],"efficiency,":[135],"while":[136],"second":[138],"further":[140],"performs":[141],"page-level":[142],"verification":[143],"on":[144,165,173],"refined":[146],"outputs":[147],"preserve":[149],"Experimental":[152],"results":[153],"show":[154],"that":[155],"our":[156,181,187],"achieves":[158],"2.78x":[160],"near-lossless":[161],"speedup":[162,172],"HunyuanOCR":[164],"OmniDocBench":[166],"v1.5":[167],"up":[169],"7.04x":[171],"long-document":[174],"tasks,":[176],"demonstrating":[177],"effectiveness":[179],"proposed":[182],"method.":[183],"We":[184],"will":[185],"release":[186],"code":[188],"facilitate":[190],"reproducibility.":[191]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2026-02-17T00:00:00"}