{"id":"https://openalex.org/W4416980068","doi":"https://doi.org/10.48550/arxiv.2512.01354","title":"The Necessity of Imperfection:Reversing Model Collapse via Simulating Cognitive Boundedness","display_name":"The Necessity of Imperfection:Reversing Model Collapse via Simulating Cognitive Boundedness","publication_year":2025,"publication_date":"2025-12-01","ids":{"openalex":"https://openalex.org/W4416980068","doi":"https://doi.org/10.48550/arxiv.2512.01354"},"language":null,"primary_location":{"id":"pmh:oai:arXiv.org:2512.01354","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.01354","pdf_url":"https://arxiv.org/pdf/2512.01354","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2512.01354","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Jiang, Zhongjie","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Jiang, Zhongjie","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/T10270","display_name":"Blockchain Technology Applications and Security","score":0.0478999987244606,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10270","display_name":"Blockchain Technology Applications and Security","score":0.0478999987244606,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T13720","display_name":"Benford\u2019s Law and Fraud Detection","score":0.04659999907016754,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10772","display_name":"Distributed systems and fault tolerance","score":0.04500000178813934,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/cognition","display_name":"Cognition","score":0.7143999934196472},{"id":"https://openalex.org/keywords/cognitive-model","display_name":"Cognitive model","score":0.483599990606308},{"id":"https://openalex.org/keywords/spurious-relationship","display_name":"Spurious relationship","score":0.4607999920845032},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4316999912261963},{"id":"https://openalex.org/keywords/cognitive-load","display_name":"Cognitive load","score":0.40220001339912415},{"id":"https://openalex.org/keywords/smoothness","display_name":"Smoothness","score":0.39750000834465027},{"id":"https://openalex.org/keywords/human-connectome-project","display_name":"Human Connectome Project","score":0.38929998874664307},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.35989999771118164}],"concepts":[{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.7143999934196472},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5784000158309937},{"id":"https://openalex.org/C161407221","wikidata":"https://www.wikidata.org/wiki/Q4382939","display_name":"Cognitive model","level":3,"score":0.483599990606308},{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.4607999920845032},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4316999912261963},{"id":"https://openalex.org/C61641136","wikidata":"https://www.wikidata.org/wiki/Q1107019","display_name":"Cognitive load","level":3,"score":0.40220001339912415},{"id":"https://openalex.org/C102634674","wikidata":"https://www.wikidata.org/wiki/Q868473","display_name":"Smoothness","level":2,"score":0.39750000834465027},{"id":"https://openalex.org/C97820695","wikidata":"https://www.wikidata.org/wiki/Q387749","display_name":"Human Connectome Project","level":3,"score":0.38929998874664307},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36090001463890076},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.35989999771118164},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.3312000036239624},{"id":"https://openalex.org/C2779151265","wikidata":"https://www.wikidata.org/wiki/Q1156791","display_name":"Copying","level":2,"score":0.32109999656677246},{"id":"https://openalex.org/C187029079","wikidata":"https://www.wikidata.org/wiki/Q958679","display_name":"Cognitive reframing","level":2,"score":0.3070000112056732},{"id":"https://openalex.org/C188147891","wikidata":"https://www.wikidata.org/wiki/Q147638","display_name":"Cognitive science","level":1,"score":0.30550000071525574},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.2935999929904938},{"id":"https://openalex.org/C81081738","wikidata":"https://www.wikidata.org/wiki/Q55542","display_name":"Lossless compression","level":3,"score":0.29159998893737793},{"id":"https://openalex.org/C169806903","wikidata":"https://www.wikidata.org/wiki/Q5937752","display_name":"Human error","level":2,"score":0.27869999408721924},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2734000086784363},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.26759999990463257},{"id":"https://openalex.org/C87868495","wikidata":"https://www.wikidata.org/wiki/Q750843","display_name":"Information processing","level":2,"score":0.265500009059906},{"id":"https://openalex.org/C105409693","wikidata":"https://www.wikidata.org/wiki/Q5937824","display_name":"Human intelligence","level":2,"score":0.26249998807907104},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2597000002861023},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.25209999084472656},{"id":"https://openalex.org/C161765866","wikidata":"https://www.wikidata.org/wiki/Q184748","display_name":"Codec","level":2,"score":0.251800000667572},{"id":"https://openalex.org/C200873422","wikidata":"https://www.wikidata.org/wiki/Q5448821","display_name":"Filling-in","level":2,"score":0.25060001015663147}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2512.01354","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.01354","pdf_url":"https://arxiv.org/pdf/2512.01354","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2512.01354","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2512.01354","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"pmh:oai:arXiv.org:2512.01354","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.01354","pdf_url":"https://arxiv.org/pdf/2512.01354","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Although":[0],"synthetic":[1,222],"data":[2,40,184,219,223],"is":[3,116],"widely":[4],"promoted":[5],"as":[6],"a":[7,47,79,93,119,132,203,229],"remedy,":[8],"its":[9],"prevailing":[10],"production":[11],"paradigm":[12,48],"--":[13,19,215,220],"one":[14],"optimizing":[15],"for":[16,142,160],"statistical":[17],"smoothness":[18],"systematically":[20],"removes":[21],"the":[22,53,60,69,176,191,235],"long-tail,":[23],"cognitively":[24,38],"grounded":[25],"irregularities":[26],"that":[27,63,84,98,180,210],"characterize":[28],"human":[29,65,138,212],"text.":[30,66],"Prolonged":[31],"training":[32],"on":[33],"such":[34],"statistically":[35],"optimal":[36],"but":[37],"impoverished":[39],"accelerates":[41],"model":[42],"collapse.":[43],"This":[44],"paper":[45],"proposes":[46],"shift:":[49],"instead":[50],"of":[51,56,78,135,205],"imitating":[52],"surface":[54,218],"properties":[55],"data,":[57],"we":[58],"simulate":[59],"cognitive":[61,90,126,161,213],"processes":[62],"generate":[64],"We":[67],"introduce":[68],"Prompt-driven":[70],"Cognitive":[71,80,94,111],"Computing":[72],"Framework":[73],"(PMCSF),":[74],"whose":[75],"core":[76],"consists":[77],"State":[81],"Decoder":[82],"(CSD)":[83],"reverse-engineers":[85],"unstructured":[86],"text":[87,103,130,139],"into":[88,102],"structured":[89],"vectors,":[91],"and":[92,151,194],"Text":[95],"Encoder":[96],"(CTE)":[97],"re-materializes":[99],"these":[100],"states":[101],"enriched":[104],"with":[105,224],"human-typical":[106],"imperfections":[107],"via":[108],"mathematically":[109],"defined":[110],"Perturbation":[112],"Operators.":[113],"The":[114],"framework":[115],"validated":[117],"through":[118],"two-stage":[120],"objective":[121],"evaluation":[122],"pipeline.":[123],"First,":[124],"in":[125,168,175],"codec":[127],"verification,":[128],"CTE":[129],"yields":[131],"Jensen-Shannon":[133],"divergence":[134],"0.0614":[136],"from":[137],"(vs.":[140],"0.4431":[141],"standard":[143],"LLM":[144],"output),":[145],"passes":[146],"double-blind":[147],"professional":[148],"media":[149],"review,":[150],"achieves":[152],"an":[153],"intraclass":[154],"correlation":[155],"coefficient":[156],"ICC":[157],"&gt;":[158],"0.9":[159],"profile":[162],"alignment":[163],"across":[164],"heterogeneous":[165],"models.":[166],"Second,":[167],"functional":[169,226],"gain":[170],"evaluation,":[171],"isomorphic":[172],"stress":[173],"tests":[174],"A-share":[177],"market":[178],"show":[179],"strategies":[181],"incorporating":[182],"CTE-generated":[183],"reduce":[185],"maximum":[186],"drawdown":[187],"by":[188,202],"47.4%":[189],"during":[190],"2015":[192],"crash":[193],"deliver":[195],"8.6%":[196],"Defensive":[197],"Alpha,":[198],"exceeding":[199],"transaction":[200],"costs":[201],"factor":[204],"33.":[206],"Our":[207],"findings":[208],"demonstrate":[209],"modelling":[211],"limitations":[214],"not":[216],"copying":[217],"enables":[221],"genuine":[225],"gain,":[227],"offering":[228],"viable":[230],"technical":[231],"pathway":[232],"toward":[233],"resolving":[234],"AI":[236],"data-collapse":[237],"crisis.":[238]},"counts_by_year":[],"updated_date":"2026-08-05T07:39:15.569665","created_date":"2025-12-03T00:00:00"}
