{"id":"https://openalex.org/W4399657780","doi":"https://doi.org/10.48550/arxiv.2406.08354","title":"DocSynthv2: A Practical Autoregressive Modeling for Document Generation","display_name":"DocSynthv2: A Practical Autoregressive Modeling for Document Generation","publication_year":2024,"publication_date":"2024-06-12","ids":{"openalex":"https://openalex.org/W4399657780","doi":"https://doi.org/10.48550/arxiv.2406.08354"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2406.08354","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2406.08354","pdf_url":"https://arxiv.org/pdf/2406.08354","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-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2406.08354","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5060424729","display_name":"Sanket Biswas","orcid":"https://orcid.org/0000-0001-6648-8270"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Biswas, Sanket","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112183701","display_name":"Rajiv Jain","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jain, Rajiv","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038267072","display_name":"Vlad I. Morariu","orcid":"https://orcid.org/0000-0001-7937-7748"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Morariu, Vlad I.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005119482","display_name":"Jiuxiang Gu","orcid":"https://orcid.org/0000-0002-3437-5084"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gu, Jiuxiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050532692","display_name":"Puneet Mathur","orcid":"https://orcid.org/0000-0002-8458-1476"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mathur, Puneet","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060359867","display_name":"Curtis Wigington","orcid":"https://orcid.org/0009-0002-2051-0043"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wigington, Curtis","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100372581","display_name":"Tong Sun","orcid":"https://orcid.org/0000-0003-3861-8933"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Tong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5065907624","display_name":"Josep Llad\u00f3s","orcid":"https://orcid.org/0000-0002-4533-4739"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Llad\u00f3s, Josep","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":8,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":1,"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":0.9847999811172485,"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":0.9847999811172485,"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/T10028","display_name":"Topic Modeling","score":0.9742000102996826,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9412999749183655,"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/autoregressive-model","display_name":"Autoregressive model","score":0.8036783933639526},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5363420844078064},{"id":"https://openalex.org/keywords/star-model","display_name":"STAR model","score":0.46822378039360046},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.3170602321624756},{"id":"https://openalex.org/keywords/autoregressive-integrated-moving-average","display_name":"Autoregressive integrated moving average","score":0.21174979209899902},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.17034175992012024},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.14085721969604492},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.13038358092308044}],"concepts":[{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.8036783933639526},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5363420844078064},{"id":"https://openalex.org/C194657046","wikidata":"https://www.wikidata.org/wiki/Q7394685","display_name":"STAR model","level":4,"score":0.46822378039360046},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3170602321624756},{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.21174979209899902},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.17034175992012024},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.14085721969604492},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.13038358092308044}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2406.08354","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2406.08354","pdf_url":"https://arxiv.org/pdf/2406.08354","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-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2406.08354","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2406.08354","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:2406.08354","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2406.08354","pdf_url":"https://arxiv.org/pdf/2406.08354","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-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4399657780.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2439807930","https://openalex.org/W2009692134","https://openalex.org/W2019155478","https://openalex.org/W1972271943","https://openalex.org/W2024529895","https://openalex.org/W2168175994","https://openalex.org/W1902630399","https://openalex.org/W2120434453","https://openalex.org/W3120578569","https://openalex.org/W1487412319"],"abstract_inverted_index":{"While":[0],"the":[1,37,69,72,76,104,109,121,142],"generation":[2,12,122,151],"of":[3,39,53,111,126,144],"document":[4,11,134,150],"layouts":[5],"has":[6],"been":[7],"extensively":[8],"explored,":[9],"comprehensive":[10],"encompassing":[13],"both":[14,54],"layout":[15,55,115],"and":[16,56,75,86,116,124,136],"content":[17,78],"presents":[18],"a":[19,31,40,60],"more":[20],"complex":[21,149],"challenge.":[22],"This":[23],"paper":[24],"delves":[25],"into":[26],"this":[27],"advanced":[28],"domain,":[29],"proposing":[30],"novel":[32],"approach":[33],"called":[34],"DocSynthv2":[35],"through":[36],"development":[38],"simple":[41],"yet":[42],"effective":[43],"autoregressive":[44,145],"structured":[45],"model.":[46],"Our":[47,139],"model,":[48],"distinct":[49],"in":[50,119,133,147],"its":[51],"integration":[52],"textual":[57,77,117],"cues,":[58],"marks":[59],"step":[61],"beyond":[62],"existing":[63],"layout-generation":[64],"approaches.":[65],"By":[66],"focusing":[67],"on":[68,93,99],"relationship":[70],"between":[71],"structural":[73],"elements":[74],"within":[79],"documents,":[80,127],"we":[81,107],"aim":[82],"to":[83],"generate":[84],"cohesive":[85],"contextually":[87],"relevant":[88],"documents":[89],"without":[90],"any":[91],"reliance":[92],"visual":[94],"components.":[95],"Through":[96],"experimental":[97],"studies":[98],"our":[100,112],"curated":[101],"benchmark":[102],"for":[103,131],"new":[105,129],"task,":[106],"demonstrate":[108],"ability":[110],"model":[113],"combining":[114],"information":[118],"enhancing":[120],"quality":[123],"relevance":[125],"opening":[128],"pathways":[130],"research":[132],"creation":[135],"automated":[137],"design.":[138],"findings":[140],"emphasize":[141],"effectiveness":[143],"models":[146],"handling":[148],"tasks.":[152]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
