{"id":"https://openalex.org/W7152630948","doi":"https://doi.org/10.1145/3774904.3792539","title":"Re-Diffusion: Modeling Latent Residuals with Diffusion for Time-Series Forecasting","display_name":"Re-Diffusion: Modeling Latent Residuals with Diffusion for Time-Series Forecasting","publication_year":2026,"publication_date":"2026-04-09","ids":{"openalex":"https://openalex.org/W7152630948","doi":"https://doi.org/10.1145/3774904.3792539"},"language":null,"primary_location":{"id":"doi:10.1145/3774904.3792539","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774904.3792539","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2026","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3774904.3792539","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5073746784","display_name":"Boning Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Boning Zhang","raw_affiliation_strings":["College of Computer Science, Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-1511-1200","affiliations":[{"raw_affiliation_string":"College of Computer Science, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047118636","display_name":"Haishuai Wang","orcid":"https://orcid.org/0000-0003-1617-0920"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haishuai Wang","raw_affiliation_strings":["College of Computer Science, Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-1617-0920","affiliations":[{"raw_affiliation_string":"College of Computer Science, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007236824","display_name":"Zehong Hu","orcid":"https://orcid.org/0000-0001-9498-161X"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zehong Hu","raw_affiliation_strings":["Alibaba Group, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-9498-161X","affiliations":[{"raw_affiliation_string":"Alibaba Group, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072545342","display_name":"J. Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiajun Wang","raw_affiliation_strings":["Alibaba Group, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-7225-9108","affiliations":[{"raw_affiliation_string":"Alibaba Group, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Hongyi Zhang","orcid":"https://orcid.org/0000-0002-2362-7805"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyi Zhang","raw_affiliation_strings":["Alibaba Group, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-2362-7805","affiliations":[{"raw_affiliation_string":"Alibaba Group, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006666486","display_name":"Jiajia Hu","orcid":"https://orcid.org/0000-0002-0372-291X"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jia Jia","raw_affiliation_strings":["Alibaba Group, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-0372-291X","affiliations":[{"raw_affiliation_string":"Alibaba Group, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"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":"7390","last_page":"7400"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.33070001006126404,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.33070001006126404,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.3019999861717224,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.09309999644756317,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.461899995803833},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.3111000061035156},{"id":"https://openalex.org/keywords/mathematical-model","display_name":"Mathematical model","score":0.2782000005245209},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.2662000060081482},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.26429998874664307}],"concepts":[{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.461899995803833},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3718000054359436},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36980000138282776},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3158000111579895},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3151000142097473},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.3111000061035156},{"id":"https://openalex.org/C76969082","wikidata":"https://www.wikidata.org/wiki/Q486902","display_name":"Mathematical model","level":2,"score":0.2782000005245209},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.2662000060081482},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.26429998874664307},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.25540000200271606}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3774904.3792539","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774904.3792539","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2026","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3774904.3792539","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774904.3792539","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2026","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Climate action","score":0.6738246083259583,"id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1498436455","https://openalex.org/W2112796928","https://openalex.org/W2128084896","https://openalex.org/W2145344497","https://openalex.org/W3134482315","https://openalex.org/W4312933868","https://openalex.org/W4389105245","https://openalex.org/W4391468387","https://openalex.org/W4393156206","https://openalex.org/W4396844322","https://openalex.org/W4403791819","https://openalex.org/W4405024802","https://openalex.org/W4415538375"],"related_works":[],"abstract_inverted_index":{"Generative":[0],"latent":[1,24,58],"diffusion":[2,25,65,115],"models":[3,103],"(LDMs)":[4],"have":[5],"been":[6],"extensively":[7],"applied":[8],"in":[9,14,120,142],"various":[10],"fields":[11],"yet":[12],"underperform":[13],"time-series":[15,34,146],"prediction.":[16],"Therefore,":[17],"We":[18],"propose":[19],"the":[20,44,47,52,55,69,112,128,143],"Re-Diffusion":[21,110,129],"model,":[22],"a":[23,39,63,132,139],"approach":[26],"that":[27,42,78,127],"generates":[28],"backbone":[29,56,85],"residuals":[30,45],"specifically":[31],"tailored":[32],"for":[33],"forecasting.":[35,147],"The":[36],"model":[37,130],"comprises":[38],"variational":[40],"autoencoder":[41],"compresses":[43],"between":[46],"actual":[48],"future":[49],"values":[50],"and":[51],"predictions":[53],"from":[54],"into":[57],"space.":[59],"It":[60],"also":[61],"includes":[62],"conditional":[64],"generator":[66],"to":[67,105,118],"forecast":[68],"potential":[70],"distribution":[71],"of":[72,96,114,145],"these":[73],"residuals.":[74],"Our":[75,123],"findings":[76],"reveal":[77],"this":[79],"latent-space":[80],"methodology":[81],"particularly":[82],"enhances":[83],"existing":[84],"predictors,":[86,137],"by":[87],"effectively":[88],"reducing":[89],"prediction":[90],"bias":[91],"through":[92],"an":[93],"advanced":[94],"estimation":[95],"complex":[97],"error":[98],"distributions.":[99],"While":[100],"previous":[101],"diffusion-based":[102],"tend":[104],"struggle":[106],"with":[107],"long-term":[108,121],"forecasting,":[109],"integrates":[111],"strengths":[113],"methods,":[116],"leading":[117],"improvements":[119],"predictions.":[122],"experimental":[124],"results":[125],"indicate":[126],"achieves":[131],"10%":[133],"promotion":[134],"over":[135],"state-of-art":[136],"marking":[138],"significant":[140],"advancement":[141],"field":[144]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-04-10T00:00:00"}