{"id":"https://openalex.org/W7163188794","doi":"https://doi.org/10.48550/arxiv.2606.02331","title":"Hallucination-Aware Diffusion Sampling for Inverse Problems via Robust Prior Updates","display_name":"Hallucination-Aware Diffusion Sampling for Inverse Problems via Robust Prior Updates","publication_year":2026,"publication_date":"2026-06-01","ids":{"openalex":"https://openalex.org/W7163188794","doi":"https://doi.org/10.48550/arxiv.2606.02331"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.02331","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.02331","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.2606.02331","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137617191","display_name":"Pengfei Jin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jin, Pengfei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014127640","display_name":"\u7530\u4e00\u6dc7","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tian, Yiqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137691203","display_name":"Kailong Fan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fan, Kailong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137670141","display_name":"Bingjie Qi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qi, Bingjie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137675446","display_name":"Quanzheng Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Quanzheng","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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.3813000023365021,"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"}},"topics":[{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.3813000023365021,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.08860000222921371,"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/T12536","display_name":"Topological and Geometric Data Analysis","score":0.06260000169277191,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/inverse","display_name":"Inverse","score":0.5960000157356262},{"id":"https://openalex.org/keywords/hallucinating","display_name":"Hallucinating","score":0.5788999795913696},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.5440000295639038},{"id":"https://openalex.org/keywords/inverse-problem","display_name":"Inverse problem","score":0.5360000133514404},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5234000086784363},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4693000018596649},{"id":"https://openalex.org/keywords/displacement","display_name":"Displacement (psychology)","score":0.4212999939918518}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6281999945640564},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.5960000157356262},{"id":"https://openalex.org/C2911011789","wikidata":"https://www.wikidata.org/wiki/Q130741","display_name":"Hallucinating","level":2,"score":0.5788999795913696},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.5440000295639038},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.5360000133514404},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5234000086784363},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.47429999709129333},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4693000018596649},{"id":"https://openalex.org/C107551265","wikidata":"https://www.wikidata.org/wiki/Q1458245","display_name":"Displacement (psychology)","level":2,"score":0.4212999939918518},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.4020000100135803},{"id":"https://openalex.org/C132878287","wikidata":"https://www.wikidata.org/wiki/Q1671727","display_name":"Inverse Gaussian distribution","level":3,"score":0.39660000801086426},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3804999887943268},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.37869998812675476},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.35350000858306885},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.35350000858306885},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31850001215934753},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3176000118255615},{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.3010999858379364},{"id":"https://openalex.org/C148043351","wikidata":"https://www.wikidata.org/wiki/Q4456944","display_name":"Current (fluid)","level":2,"score":0.29660001397132874},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.27480000257492065},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.26660001277923584},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.25290000438690186}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.02331","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.02331","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.2606.02331","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.02331","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":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.4221658706665039}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Diffusion-based":[0],"inverse":[1,48,123,200],"problem":[2],"solvers":[3,49],"can":[4,62,194],"produce":[5],"realistic":[6],"reconstructions,":[7],"but":[8,178],"realism":[9],"alone":[10],"does":[11],"not":[12],"ensure":[13],"that":[14,33,59,87],"the":[15,21,40,65,69,89,93,98,102,107,171,191,204],"recovered":[16],"details":[17],"are":[18],"supported":[19],"by":[20,75],"measurement.":[22],"We":[23,111],"study":[24,175],"this":[25,76],"failure":[26],"as":[27],"measurement-conditioned":[28],"hallucination:":[29],"visually":[30],"meaningful":[31],"content":[32,61],"is":[34,72,176],"either":[35],"implausible":[36],"or":[37],"inconsistent":[38],"with":[39],"measured":[41],"instance.":[42],"Our":[43],"analysis":[44],"separates":[45],"Bayes-rule-based":[46],"diffusion":[47,94,199],"into":[50],"a":[51,55,84,187],"prior":[52,95,192,205],"update":[53,109,193],"and":[54,105,116,121,128,137,146,160],"measurement-conditioning":[56],"step,":[57],"showing":[58],"hallucinated":[60],"enter":[63],"through":[64],"prior-side":[66],"proposal":[67],"before":[68],"measurement":[70,108],"correction":[71],"applied.":[73],"Motivated":[74],"view,":[77],"we":[78],"propose":[79],"Robust":[80],"Prior":[81],"Update":[82],"(RPU),":[83],"solver-level":[85],"module":[86],"probes":[88],"local":[90],"stability":[91],"of":[92,155,162],"update,":[96],"re-anchors":[97],"resulting":[99],"displacement":[100],"at":[101],"current":[103],"iterate,":[104],"leaves":[106],"unchanged.":[110],"instantiate":[112],"RPU":[113,134,152,180],"in":[114,198],"DPS":[115,140],"evaluate":[117],"it":[118],"on":[119,166],"FFHQ":[120,167],"ImageNet":[122,172],"problems":[124],"using":[125],"automatic":[126],"metrics":[127],"human":[129,150],"faithfulness":[130,197],"studies.":[131],"On":[132],"FFHQ,":[133],"improves":[135],"PSNR":[136],"LPIPS":[138],"over":[139],"across":[141],"box":[142,168],"inpainting,":[143,169],"Gaussian":[144,173],"deblurring,":[145],"motion":[147],"deblurring.":[148],"In":[149],"judgments,":[151],"receives":[153],"91.9%":[154],"blind":[156],"non-tie":[157,164,182],"majority":[158],"preferences":[159,165],"91.1%":[161],"ground-truth-assisted":[163],"while":[170],"reader":[174],"tie-heavy":[177],"favors":[179],"among":[181],"cases.":[183],"These":[184],"results":[185],"support":[186],"targeted":[188],"claim:":[189],"robustifying":[190],"improve":[195],"instance":[196],"solvers,":[201],"especially":[202],"when":[203],"shapes":[206],"weakly":[207],"constrained":[208],"content.":[209]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-03T00:00:00"}