{"id":"https://openalex.org/W7129438448","doi":"https://doi.org/10.48550/arxiv.2602.14469","title":"Measuring and Mitigating Post-hoc Rationalization in Reverse Chain-of-Thought Generation","display_name":"Measuring and Mitigating Post-hoc Rationalization in Reverse Chain-of-Thought Generation","publication_year":2026,"publication_date":"2026-02-16","ids":{"openalex":"https://openalex.org/W7129438448","doi":"https://doi.org/10.48550/arxiv.2602.14469"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.14469","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5036172405","display_name":"Guangyue Peng","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Peng, Guangyue","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030184172","display_name":"Zongchao Chen","orcid":"https://orcid.org/0000-0001-6383-3729"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Zongchao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126277379","display_name":"Wen Luo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Wen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111283466","display_name":"Yuntao Wen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wen, Yuntao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126223396","display_name":"Wei Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Wei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057222111","display_name":"Ren Feng","orcid":"https://orcid.org/0000-0002-7352-8127"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Feng, Ruixiang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017649041","display_name":"Ran Le","orcid":"https://orcid.org/0009-0006-6010-6781"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Le, Ran","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126251844","display_name":"Chen Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Chen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125962568","display_name":"Zhenwei An","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"An, Zhenwei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126227147","display_name":"Yang Song","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Yang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126213777","display_name":"Tao Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Tao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5126254793","display_name":"Houfeng Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Houfeng","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":12,"corresponding_author_ids":["https://openalex.org/A5036172405"],"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":0.5641000270843506,"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":0.5641000270843506,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.07859999686479568,"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/T10906","display_name":"AI-based Problem Solving and Planning","score":0.021400000900030136,"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/probabilistic-logic","display_name":"Probabilistic logic","score":0.7914000153541565},{"id":"https://openalex.org/keywords/rationalization","display_name":"Rationalization (economics)","score":0.552299976348877},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.4814999997615814},{"id":"https://openalex.org/keywords/axiom","display_name":"Axiom","score":0.4652000069618225},{"id":"https://openalex.org/keywords/cognition","display_name":"Cognition","score":0.4074000120162964},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.3921000063419342},{"id":"https://openalex.org/keywords/phenomenon","display_name":"Phenomenon","score":0.349700003862381}],"concepts":[{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.7914000153541565},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6212000250816345},{"id":"https://openalex.org/C52438962","wikidata":"https://www.wikidata.org/wiki/Q1555139","display_name":"Rationalization (economics)","level":2,"score":0.552299976348877},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.4814999997615814},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47519999742507935},{"id":"https://openalex.org/C167729594","wikidata":"https://www.wikidata.org/wiki/Q17736","display_name":"Axiom","level":2,"score":0.4652000069618225},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.4074000120162964},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3921000063419342},{"id":"https://openalex.org/C50335755","wikidata":"https://www.wikidata.org/wiki/Q483247","display_name":"Phenomenon","level":2,"score":0.349700003862381},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.34439998865127563},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.33880001306533813},{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.3160000145435333},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3050999939441681},{"id":"https://openalex.org/C9679016","wikidata":"https://www.wikidata.org/wiki/Q1417473","display_name":"Principle of maximum entropy","level":2,"score":0.2976999878883362},{"id":"https://openalex.org/C61641136","wikidata":"https://www.wikidata.org/wiki/Q1107019","display_name":"Cognitive load","level":3,"score":0.2971000075340271},{"id":"https://openalex.org/C88626702","wikidata":"https://www.wikidata.org/wiki/Q1128903","display_name":"Continuation","level":2,"score":0.27160000801086426},{"id":"https://openalex.org/C18483071","wikidata":"https://www.wikidata.org/wiki/Q168432","display_name":"Anchoring","level":2,"score":0.2581000030040741},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2524000108242035}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.14469","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2602.14469","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.14469","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:doi:10.48550/arxiv.2602.14469","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"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":{"Reverse":[0],"Chain-of-Thought":[1],"Generation":[2],"(RCG)":[3],"synthesizes":[4],"reasoning":[5,191],"traces":[6,182],"from":[7,100],"query-answer":[8],"pairs,":[9],"but":[10],"runs":[11],"the":[12,22,26,35,67,76,111,152],"risk":[13],"of":[14,110],"producing":[15],"post-hoc":[16],"rationalizations:":[17],"when":[18],"models":[19,73,178],"can":[20],"see":[21],"answer":[23,27,60,160],"during":[24],"generation,":[25],"serves":[28],"as":[29],"a":[30,43,130],"cognitive":[31,101],"anchor":[32],"that":[33,71,133,194],"shapes":[34],"entire":[36],"explanation.":[37],"We":[38,63,170],"formalize":[39],"this":[40,105,122,143],"phenomenon":[41],"through":[42],"three-level":[44],"measurement":[45],"hierarchy:":[46],"lexical,":[47],"entropic,":[48],"and":[49,58,92],"probabilistic":[50,93],"anchoring,":[51],"each":[52],"captures":[53],"surface":[54],"artifacts,":[55],"entropy":[56],"dynamics,":[57],"latent":[59],"dependence,":[61],"respectively.":[62],"analyze":[64],"semantic":[65],"suppression,":[66],"intuitive":[68],"mitigation":[69],"strategy":[70],"instructs":[72],"to":[74,78,107,145,155,183,198],"ignore":[75],"answer,":[77,113],"find":[79],"out":[80],"its":[81],"counterproduction:":[82],"while":[83,204],"it":[84,88],"reduces":[85,164],"lexical":[86],"overlap,":[87],"paradoxically":[89],"increases":[90],"entropic":[91],"anchoring.":[94],"Drawing":[95],"on":[96,118,179],"Ironic":[97],"Process":[98],"Theory":[99],"psychology,":[102],"we":[103,124],"attribute":[104],"failure":[106],"active":[108],"monitoring":[109],"forbidden":[112],"which":[114,176],"inadvertently":[115],"deepens":[116],"dependence":[117],"it.":[119],"To":[120],"break":[121],"cycle,":[123],"propose":[125],"Structural":[126],"Skeleton-guided":[127],"Reasoning":[128],"(SSR),":[129],"two-phase":[131],"approach":[132],"first":[134],"generates":[135],"an":[136],"answer-invariant":[137],"functional":[138],"skeleton":[139,144],"structure,":[140],"then":[141],"uses":[142],"guide":[146],"full":[147],"trace":[148],"generation.":[149],"By":[150],"redirecting":[151],"information":[153],"flow":[154],"structural":[156,186],"planning":[157],"rather":[158],"than":[159],"monitoring,":[161],"SSR":[162,174,181],"consistently":[163],"anchoring":[165],"across":[166,189],"all":[167],"three":[168],"levels.":[169],"further":[171],"introduce":[172],"Distilled":[173],"(SSR-D),":[175],"fine-tunes":[177],"teacher-generated":[180],"ensure":[184],"reliable":[185],"adherence.":[187],"Experiments":[188],"open-ended":[190],"benchmarks":[192],"demonstrate":[193],"SSR-D":[195],"achieves":[196],"up":[197],"10%":[199],"improvement":[200],"over":[201],"suppression":[202],"baselines":[203],"preserving":[205],"out-of-distribution":[206],"(OOD)":[207],"generalization.":[208]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2026-02-18T00:00:00"}