{"id":"https://openalex.org/W4412888889","doi":"https://doi.org/10.18653/v1/2025.findings-acl.38","title":"Probing the Geometry of Truth: Consistency and Generalization of Truth Directions in LLMs Across Logical Transformations and Question Answering Tasks","display_name":"Probing the Geometry of Truth: Consistency and Generalization of Truth Directions in LLMs Across Logical Transformations and Question Answering Tasks","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412888889","doi":"https://doi.org/10.18653/v1/2025.findings-acl.38"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2025.findings-acl.38","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.38","pdf_url":"https://aclanthology.org/2025.findings-acl.38.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: ACL 2025","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.findings-acl.38.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5110921325","display_name":"Yinghui Bao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuntai Bao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101722406","display_name":"Xuhong Zhang","orcid":"https://orcid.org/0000-0002-8571-9780"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xuhong Zhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102448448","display_name":"Tianyu Du","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tianyu Du","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101765691","display_name":"Xinkui Zhao","orcid":"https://orcid.org/0000-0002-1115-5652"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xinkui Zhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109705360","display_name":"Z. Y. Feng","orcid":"https://orcid.org/0009-0000-4283-5135"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhengwen Feng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079854850","display_name":"Hao Peng","orcid":"https://orcid.org/0000-0001-5320-3117"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hao Peng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5069353502","display_name":"Jianwei Yin","orcid":"https://orcid.org/0000-0003-4703-7348"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jianwei Yin","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":1.673,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.83457347,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"682","last_page":"700"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10215","display_name":"Semantic Web and Ontologies","score":0.989799976348877,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.989799976348877,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9818000197410583,"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/T10456","display_name":"Multi-Agent Systems and Negotiation","score":0.9564999938011169,"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/generalization","display_name":"Generalization","score":0.7801437377929688},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.7037214636802673},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5398828387260437},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.45909935235977173},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45415985584259033},{"id":"https://openalex.org/keywords/epistemology","display_name":"Epistemology","score":0.4003351330757141},{"id":"https://openalex.org/keywords/calculus","display_name":"Calculus (dental)","score":0.3303779363632202},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32325389981269836},{"id":"https://openalex.org/keywords/philosophy","display_name":"Philosophy","score":0.1870536208152771}],"concepts":[{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.7801437377929688},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.7037214636802673},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5398828387260437},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.45909935235977173},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45415985584259033},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.4003351330757141},{"id":"https://openalex.org/C2777686260","wikidata":"https://www.wikidata.org/wiki/Q144037","display_name":"Calculus (dental)","level":2,"score":0.3303779363632202},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32325389981269836},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.1870536208152771},{"id":"https://openalex.org/C199343813","wikidata":"https://www.wikidata.org/wiki/Q12128","display_name":"Dentistry","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.findings-acl.38","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.38","pdf_url":"https://aclanthology.org/2025.findings-acl.38.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: ACL 2025","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.findings-acl.38","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.38","pdf_url":"https://aclanthology.org/2025.findings-acl.38.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: ACL 2025","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.5899999737739563,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G4644492335","display_name":null,"funder_award_id":"62402418","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412888889.pdf","grobid_xml":"https://content.openalex.org/works/W4412888889.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3162204513","https://openalex.org/W4295532600","https://openalex.org/W2063823869","https://openalex.org/W2047973478","https://openalex.org/W2067569035","https://openalex.org/W2371138613","https://openalex.org/W2090985514","https://openalex.org/W2048963458","https://openalex.org/W43109613","https://openalex.org/W2359952343"],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2],"(LLMs)":[3],"are":[4,62],"trained":[5,108],"on":[6,109],"extensive":[7],"datasets":[8],"that":[9,23,80,105],"encapsulate":[10],"substantial":[11],"world":[12],"knowledge.However,":[13],"their":[14,139],"outputs":[15],"often":[16],"include":[17],"confidently":[18],"stated":[19],"inaccuracies.Earlier":[20],"works":[21],"suggest":[22],"LLMs":[24,51,83],"encode":[25],"truthfulness":[26,39,106,133],"as":[27],"a":[28],"distinct":[29],"linear":[30],"feature,":[31],"termed":[32],"the":[33,46,71,98,129,160],"\"truth":[34],"direction\",":[35],"which":[36],"can":[37,113],"classify":[38],"reliably.We":[40],"address":[41],"several":[42],"open":[43],"questions":[44],"about":[45],"truth":[47,55,66,72,86,153],"direction:":[48],"(i)":[49],"whether":[50,58],"universally":[52],"exhibit":[53,84],"consistent":[54,85],"directions;":[56,67],"(ii)":[57],"sophisticated":[59],"probing":[60],"techniques":[61],"necessary":[63],"to":[64,116,141],"identify":[65],"and":[68,123,155],"(iii)":[69],"how":[70],"direction":[73],"generalizes":[74],"across":[75],"diverse":[76],"contexts.Our":[77],"findings":[78],"reveal":[79],"not":[81],"all":[82],"directions,":[87],"with":[88],"stronger":[89],"representations":[90,162],"observed":[91],"in":[92,97,135,145],"more":[93],"capable":[94],"models,":[95],"particularly":[96],"context":[99],"of":[100,132,152,163],"logical":[101,117],"negation.Additionally,":[102],"we":[103,127],"demonstrate":[104],"probes":[107,134],"declarative":[110],"atomic":[111],"statements":[112],"generalize":[114],"effectively":[115],"transformations,":[118],"question-answering":[119],"tasks,":[120],"in-context":[121],"learning,":[122],"external":[124],"knowledge":[125],"sources.Finally,":[126],"explore":[128],"practical":[130],"application":[131],"selective":[136],"question-answering,":[137],"illustrating":[138],"potential":[140],"improve":[142],"user":[143],"trust":[144],"LLM":[146,164],"outputs.These":[147],"results":[148],"advance":[149],"our":[150],"understanding":[151],"directions":[154],"provide":[156],"new":[157],"insights":[158],"into":[159],"internal":[161],"beliefs.":[165]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}