{"id":"https://openalex.org/W7155054053","doi":"https://doi.org/10.48550/arxiv.2604.17884","title":"SPREG: Structured Plan Repair with Entropy-Guided Test-Time Intervention for Large Language Model Reasoning","display_name":"SPREG: Structured Plan Repair with Entropy-Guided Test-Time Intervention for Large Language Model Reasoning","publication_year":2026,"publication_date":"2026-04-20","ids":{"openalex":"https://openalex.org/W7155054053","doi":"https://doi.org/10.48550/arxiv.2604.17884"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.17884","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.17884","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.2604.17884","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134180426","display_name":"Xuan Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Xuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134178025","display_name":"Yu Ming","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ming, Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134199073","display_name":"Xinhao Zhong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhong, Xinhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126603170","display_name":"Xinyu Yu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Xinyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134170027","display_name":"Wenjie Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Wenjie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134175237","display_name":"Shuai Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Shuai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134106072","display_name":"Wei Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Wei","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":0.2313999980688095,"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":0.2313999980688095,"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":0.13660000264644623,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.09290000051259995,"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/language-model","display_name":"Language model","score":0.5698000192642212},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5636000037193298},{"id":"https://openalex.org/keywords/cross-entropy","display_name":"Cross entropy","score":0.42170000076293945},{"id":"https://openalex.org/keywords/plan","display_name":"Plan (archaeology)","score":0.4214000105857849},{"id":"https://openalex.org/keywords/implementation","display_name":"Implementation","score":0.36230000853538513},{"id":"https://openalex.org/keywords/logical-reasoning","display_name":"Logical reasoning","score":0.33980000019073486}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7010999917984009},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.5698000192642212},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5636000037193298},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4771000146865845},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4255000054836273},{"id":"https://openalex.org/C167981619","wikidata":"https://www.wikidata.org/wiki/Q1685498","display_name":"Cross entropy","level":3,"score":0.42170000076293945},{"id":"https://openalex.org/C2776505523","wikidata":"https://www.wikidata.org/wiki/Q4785468","display_name":"Plan (archaeology)","level":2,"score":0.4214000105857849},{"id":"https://openalex.org/C26713055","wikidata":"https://www.wikidata.org/wiki/Q245962","display_name":"Implementation","level":2,"score":0.36230000853538513},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3499000072479248},{"id":"https://openalex.org/C43971567","wikidata":"https://www.wikidata.org/wiki/Q3142865","display_name":"Logical reasoning","level":2,"score":0.33980000019073486},{"id":"https://openalex.org/C9679016","wikidata":"https://www.wikidata.org/wiki/Q1417473","display_name":"Principle of maximum entropy","level":2,"score":0.3361000120639801},{"id":"https://openalex.org/C90312973","wikidata":"https://www.wikidata.org/wiki/Q7449052","display_name":"Semantic data model","level":2,"score":0.32710000872612},{"id":"https://openalex.org/C89288958","wikidata":"https://www.wikidata.org/wiki/Q7301504","display_name":"Reasoning system","level":2,"score":0.2946999967098236},{"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/C134752490","wikidata":"https://www.wikidata.org/wiki/Q374182","display_name":"Logical consequence","level":2,"score":0.27489998936653137},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.257999986410141}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.17884","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.17884","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.2604.17884","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.17884","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/4","score":0.5751163363456726,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"Language":[1],"Models":[2],"(LLMs)":[3],"are":[4],"prone":[5],"to":[6,55,93,105],"logical":[7,67],"hallucinations":[8],"and":[9,30],"stochastic":[10],"drifts":[11],"during":[12],"long-chain":[13],"reasoning.":[14],"While":[15],"Classifier-Free":[16],"Guidance":[17],"(CFG)":[18],"can":[19],"improve":[20],"instruction":[21],"adherence,":[22],"standard":[23],"static":[24],"implementations":[25],"often":[26],"cause":[27],"semantic":[28],"dilution":[29],"linguistic":[31],"degradation.":[32],"We":[33],"propose":[34],"SPREG":[35,49,100],"(Structured":[36],"Plan-guided":[37],"Real-time":[38],"Entropy":[39],"Gating),":[40],"a":[41,73,106,118],"lightweight":[42],"inference-time":[43],"framework":[44],"for":[45],"surgical":[46],"error":[47],"rectification.":[48],"employs":[50],"an":[51],"adaptive":[52],"dual-threshold":[53],"mechanism":[54],"monitor":[56],"real-time":[57],"entropy,":[58],"identifying":[59],"sudden":[60],"``entropy":[61],"spikes''":[62],"as":[63],"reliable":[64],"indicators":[65],"of":[66],"failure.":[68],"Upon":[69],"detection,":[70],"it":[71],"triggers":[72],"dynamic":[74],"repair":[75],"by":[76],"replacing":[77],"uninformative":[78],"null-priors":[79],"with":[80],"reference":[81],"distributions":[82],"synthesized":[83],"from":[84],"historical":[85],"high-confidence":[86],"states.":[87],"By":[88],"modulating":[89],"guidance":[90],"intensity":[91],"according":[92],"structured":[94],"reasoning":[95],"stages":[96],"(e.g.,":[97],"Action,":[98],"Observation),":[99],"steers":[101],"the":[102],"model":[103],"back":[104],"stable":[107],"manifold":[108],"without":[109],"compromising":[110],"fluency.":[111],"Our":[112],"experiments":[113],"demonstrate":[114],"significant":[115],"gains,":[116],"notably":[117],"20.0%":[119],"absolute":[120],"accuracy":[121],"improvement":[122],"on":[123],"AIME25,":[124],"while":[125],"effectively":[126],"suppressing":[127],"uncontrolled":[128],"entropy":[129],"drift":[130],"in":[131],"complex":[132],"tasks.":[133]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-22T00:00:00"}