{"id":"https://openalex.org/W7147497143","doi":"https://doi.org/10.48550/arxiv.2603.26675","title":"GeoBlock: Inferring Block Granularity from Dependency Geometry in Diffusion Language Models","display_name":"GeoBlock: Inferring Block Granularity from Dependency Geometry in Diffusion Language Models","publication_year":2026,"publication_date":"2026-03-04","ids":{"openalex":"https://openalex.org/W7147497143","doi":"https://doi.org/10.48550/arxiv.2603.26675"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.26675","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.26675","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2603.26675","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5132713729","display_name":"Lipeng Wan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wan, Lipeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132596773","display_name":"Junjie Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Junjie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128245197","display_name":"Jianhui Gu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gu, Jianhui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132593086","display_name":"Zeyang Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Zeyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132713441","display_name":"Xuyang Lu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Xuyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5132682449","display_name":"Xuguang Lan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lan, Xuguang","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/T12090","display_name":"Language and cultural evolution","score":0.23510000109672546,"subfield":{"id":"https://openalex.org/subfields/3316","display_name":"Cultural Studies"},"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/T12090","display_name":"Language and cultural evolution","score":0.23510000109672546,"subfield":{"id":"https://openalex.org/subfields/3316","display_name":"Cultural Studies"},"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":0.15690000355243683,"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/T10465","display_name":"Neurobiology of Language and Bilingualism","score":0.08659999817609787,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.857200026512146},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.8252000212669373},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.6460000276565552},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.49410000443458557},{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.4912000000476837},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.42289999127388},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.39489999413490295}],"concepts":[{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.857200026512146},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.8252000212669373},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.6460000276565552},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6261000037193298},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.49459999799728394},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.49410000443458557},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.4912000000476837},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4453999996185303},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.42289999127388},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.39489999413490295},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.288100004196167},{"id":"https://openalex.org/C2779982251","wikidata":"https://www.wikidata.org/wiki/Q25053762","display_name":"Stochastic block model","level":3,"score":0.28519999980926514},{"id":"https://openalex.org/C41431624","wikidata":"https://www.wikidata.org/wiki/Q1053357","display_name":"Block size","level":3,"score":0.2793999910354614},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.2703999876976013},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.27000001072883606},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2648000121116638},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26409998536109924},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.2619999945163727},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.25999999046325684},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.25279998779296875}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.26675","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.26675","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.26675","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.26675","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Block":[0],"diffusion":[1,7,52,130,150,171],"enables":[2],"efficient":[3],"parallel":[4,67,126],"refinement":[5,105,134],"in":[6],"language":[8],"models,":[9],"but":[10],"its":[11],"decoding":[12],"behavior":[13],"depends":[14],"critically":[15],"on":[16,23,89],"block":[17,74,79,111,117,129,149,163,170],"size.":[18],"Existing":[19],"block-sizing":[20],"strategies":[21],"rely":[22],"fixed":[24],"rules":[25],"or":[26,92],"heuristic":[27],"signals":[28],"and":[29,107,144,165],"do":[30],"not":[31],"account":[32],"for":[33],"the":[34,120,125,167],"dependency":[35,84,99,121],"geometry":[36,49],"that":[37,77,135,158],"determines":[38,78,109],"which":[39],"tokens":[40],"can":[41],"be":[42],"safely":[43],"refined":[44],"together.":[45],"This":[46],"motivates":[47],"a":[48,72,174],"view":[50],"of":[51,87,128,169],"decoding:":[53],"\\emph{regions":[54],"with":[55,172],"strong":[56],"causal":[57],"ordering":[58],"require":[59],"sequential":[60],"updates,":[61],"whereas":[62],"semantically":[63],"cohesive":[64],"regions":[65,106],"admit":[66],"refinement.}":[68],"We":[69],"introduce":[70],"GeoBlock,":[71],"geometry-aware":[73],"inference":[75],"framework":[76],"granularity":[80,118],"directly":[81],"from":[82],"attention-derived":[83],"geometry.":[85],"Instead":[86],"relying":[88],"predefined":[90],"schedules":[91],"local":[93],"confidence":[94],"heuristics,":[95],"GeoBlock":[96,123,139,159],"analyzes":[97],"cross-token":[98],"patterns":[100],"to":[101,119],"identify":[102],"geometrically":[103],"stable":[104],"dynamically":[108],"appropriate":[110],"boundaries":[112,164],"during":[113],"decoding.":[114],"By":[115],"adapting":[116],"geometry,":[122],"preserves":[124],"efficiency":[127],"while":[131],"enforcing":[132],"dependency-consistent":[133],"exhibits":[136],"autoregressive":[137],"reliability.":[138],"requires":[140],"no":[141],"additional":[142,176],"training":[143],"integrates":[145],"seamlessly":[146],"into":[147],"existing":[148],"architectures.":[151],"Extensive":[152],"experiments":[153],"across":[154],"multiple":[155],"benchmarks":[156],"show":[157],"reliably":[160],"identifies":[161],"geometry-consistent":[162],"improves":[166],"accuracy":[168],"only":[173],"small":[175],"computational":[177],"budget.":[178]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-02T00:00:00"}
