{"id":"https://openalex.org/W7172331611","doi":"https://doi.org/10.48550/arxiv.2607.28908","title":"Reflection or Re-Generation? Why LLM Revision Fails Where Human Revision Succeeds","display_name":"Reflection or Re-Generation? Why LLM Revision Fails Where Human Revision Succeeds","publication_year":2026,"publication_date":"2026-07-31","ids":{"openalex":"https://openalex.org/W7172331611","doi":"https://doi.org/10.48550/arxiv.2607.28908"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.28908","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.28908","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":null,"license_id":null,"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.2607.28908","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113175129","display_name":"Yefan Tao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tao, Yefan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119821005","display_name":"Gerald Friedland","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Friedland, Gerald","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083020961","display_name":"M. Chandrasekaran","orcid":"https://orcid.org/0000-0002-6803-2645"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chandrasekaran, Madhusudhanan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5144297523","display_name":"Luyang Kong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kong, Luyang","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/T10028","display_name":"Topic Modeling","score":0.3334999978542328,"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/T10028","display_name":"Topic Modeling","score":0.3334999978542328,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.09359999746084213,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T13629","display_name":"Text Readability and Simplification","score":0.09070000052452087,"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/reflection","display_name":"Reflection (computer programming)","score":0.7642999887466431},{"id":"https://openalex.org/keywords/oracle","display_name":"Oracle","score":0.7062000036239624},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6176000237464905},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.4034000039100647},{"id":"https://openalex.org/keywords/protocol","display_name":"Protocol (science)","score":0.390500009059906},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.3573000133037567},{"id":"https://openalex.org/keywords/human-error","display_name":"Human error","score":0.34139999747276306}],"concepts":[{"id":"https://openalex.org/C65682993","wikidata":"https://www.wikidata.org/wiki/Q1056451","display_name":"Reflection (computer programming)","level":2,"score":0.7642999887466431},{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.7062000036239624},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6176000237464905},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.4625000059604645},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.45660001039505005},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.43810001015663147},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.4034000039100647},{"id":"https://openalex.org/C2780385302","wikidata":"https://www.wikidata.org/wiki/Q367158","display_name":"Protocol (science)","level":3,"score":0.390500009059906},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37450000643730164},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.3573000133037567},{"id":"https://openalex.org/C169806903","wikidata":"https://www.wikidata.org/wiki/Q5937752","display_name":"Human error","level":2,"score":0.34139999747276306},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.3357999920845032},{"id":"https://openalex.org/C167085575","wikidata":"https://www.wikidata.org/wiki/Q6803654","display_name":"Mean squared prediction error","level":2,"score":0.3296999931335449},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.3278999924659729},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.3174000084400177},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.3073999881744385},{"id":"https://openalex.org/C2778023277","wikidata":"https://www.wikidata.org/wiki/Q321703","display_name":"Premise","level":2,"score":0.29319998621940613},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2815000116825104},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2782000005245209},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2777999937534332},{"id":"https://openalex.org/C103088060","wikidata":"https://www.wikidata.org/wiki/Q1062839","display_name":"Error detection and correction","level":2,"score":0.2754000127315521},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.257999986410141},{"id":"https://openalex.org/C59656382","wikidata":"https://www.wikidata.org/wiki/Q191536","display_name":"Conjunction (astronomy)","level":2,"score":0.25369998812675476}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.28908","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.28908","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2607.28908","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.28908","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":null,"license_id":null,"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":{"Reflection,":[0],"the":[1,36,115,130,133,198,223],"ability":[2],"to":[3,11,24,132,173],"revisit":[4],"and":[5,47,56,152,167,190,203],"revise":[6],"prior":[7],"reasoning,":[8],"is":[9,179,212,228],"central":[10],"how":[12],"humans":[13],"improve":[14],"their":[15],"answers.":[16],"Large":[17],"language":[18],"models":[19,202],"(LLMs)":[20],"are":[21],"increasingly":[22],"prompted":[23],"\"reflect,\"":[25],"yet":[26],"whether":[27],"this":[28],"resembles":[29],"human":[30,46,143],"revision":[31,49,134,154,218],"remains":[32],"unclear.":[33],"We":[34],"introduce":[35],"Human-LLM":[37],"Reflection":[38],"Framework":[39],"(HRF),":[40],"a":[41,156,174],"controlled":[42],"two-pass":[43],"protocol":[44],"comparing":[45],"LLM":[48,74,226],"under":[50,192],"identical":[51],"conditions":[52],"across":[53],"self-,":[54],"peer-,":[55],"cross-agent":[57],"settings.":[58,126],"Using":[59],"an":[60,193],"information-theoretic":[61],"analysis":[62],"based":[63],"on":[64,149,181,187],"per-iteration":[65],"cross-entropy":[66],"reduction,":[67],"we":[68],"find":[69],"two":[70],"failure":[71,131],"modes":[72],"of":[73],"reflection.":[75],"On":[76,99],"objective":[77,182],"tasks":[78,184],"with":[79],"finite":[80],"answer":[81],"spaces,":[82],"reflection":[83,227],"yields":[84,103,121],"near-zero":[85],"information":[86],"gain":[87,106,123],"(Delta":[88,107],"I":[89,108],"approx":[90],"0),":[91,110],"behaving":[92],"as":[93,231,235],"neutral":[94],"re-generation":[95,233],"indistinguishable":[96],"from":[97,114],"re-sampling.":[98],"subjective":[100,188],"tasks,":[101],"it":[102,206],"significant":[104],"negative":[105],"<":[109],"moving":[111],"predictions":[112],"away":[113],"target.":[116],"Human":[117],"revision,":[118],"by":[119,165,168],"contrast,":[120],"positive":[122],"in":[124],"both":[125],"Cross-agent":[127],"experiments":[128],"localize":[129],"step,":[135],"not":[136],"input":[137],"quality:":[138],"LLMs":[139],"degrade":[140],"even":[141],"high-quality":[142],"responses.":[144],"Diagnostic":[145],"analyses":[146],"(revision":[147],"conditioned":[148,232],"first-pass":[150],"correctness,":[151],"oracle-guided":[153],"against":[155],"random-reshuffle":[157],"baseline)":[158],"show":[159],"that":[160],"which":[161],"sub-step":[162],"dominates":[163],"varies":[164],"task":[166],"model":[169],"rather":[170],"than":[171,234],"reducing":[172],"single":[175],"mechanism:":[176],"self-error":[177],"detection":[178],"present":[180],"multiple-choice":[183],"but":[185],"weak":[186],"ones,":[189],"recovery":[191],"oracle":[194],"error":[195],"signal":[196],"exceeds":[197],"baseline":[199],"for":[200,207],"some":[201],"falls":[204],"below":[205],"others.":[208],"The":[209],"unifying":[210],"account":[211],"structural:":[213],"without":[214],"external":[215],"information,":[216],"self-conditioned":[217],"cannot":[219],"reduce":[220],"uncertainty":[221],"about":[222],"target,":[224],"so":[225],"better":[229],"understood":[230],"genuine":[236],"error-driven":[237],"revision.":[238]},"counts_by_year":[],"updated_date":"2026-08-04T08:18:43.703281","created_date":"2026-08-04T00:00:00"}