{"id":"https://openalex.org/W7166818995","doi":"https://doi.org/10.18653/v1/2026.findings-acl.1442","title":"CARO: Chain-of-Analogy Reasoning Optimization for Robust Content Moderation","display_name":"CARO: Chain-of-Analogy Reasoning Optimization for Robust Content Moderation","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7166818995","doi":"https://doi.org/10.18653/v1/2026.findings-acl.1442"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2026.findings-acl.1442","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.1442","pdf_url":"https://aclanthology.org/2026.findings-acl.1442.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 2026","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2026.findings-acl.1442.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5040323946","display_name":"Bingzhe Wu","orcid":"https://orcid.org/0000-0001-9598-7642"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bingzhe Wu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133556981","display_name":"Haotian Lu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haotian Lu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139755276","display_name":"Yuchen Mou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuchen Mou","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":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.80846367,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"28880","last_page":"28892"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12262","display_name":"Hate Speech and Cyberbullying Detection","score":0.6287999749183655,"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/T12262","display_name":"Hate Speech and Cyberbullying Detection","score":0.6287999749183655,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.05860000103712082,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.05490000173449516,"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/relation","display_name":"Relation (database)","score":0.3447999954223633},{"id":"https://openalex.org/keywords/content","display_name":"Content (measure theory)","score":0.322299987077713},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.29600000381469727},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.2784999907016754},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.2709999978542328}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5077000260353088},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4002000093460083},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.3447999954223633},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.326200008392334},{"id":"https://openalex.org/C2778152352","wikidata":"https://www.wikidata.org/wiki/Q5165061","display_name":"Content (measure theory)","level":2,"score":0.322299987077713},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.29600000381469727},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2784999907016754},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.2709999978542328},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.263700008392334},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.260699987411499}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2026.findings-acl.1442","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.1442","pdf_url":"https://aclanthology.org/2026.findings-acl.1442.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 2026","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2026.findings-acl.1442","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.1442","pdf_url":"https://aclanthology.org/2026.findings-acl.1442.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 2026","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7166818995.pdf","grobid_xml":"https://content.openalex.org/works/W7166818995.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Current":[0],"large":[1],"language":[2],"models":[3,107,113],"(LLMs),":[4],"even":[5],"those":[6],"explicitly":[7],"trained":[8],"for":[9],"reasoning,":[10],"often":[11],"struggle":[12],"with":[13],"ambiguous":[14,132],"content":[15],"moderation":[16,61,112,133],"cases":[17],"due":[18],"to":[19,44,77],"misleading":[20],"\"decision":[21],"shortcuts\"":[22],"embedded":[23],"in":[24,49],"context.Inspired":[25],"by":[26],"cognitive":[27],"psychology":[28],"insights":[29],"into":[30],"expert":[31],"moderation,":[32],"we":[33,68],"introduce":[34],"CARO":[35,51,86,102],"(Chain-of-Analogy":[36],"Reasoning":[37],"Optimization),":[38],"a":[39,70],"novel":[40],"two-stage":[41],"training":[42],"framework":[43],"induce":[45],"robust":[46],"analogical":[47,53,79,90],"reasoning":[48,54,80,106],"LLMs.First,":[50],"bootstraps":[52],"chains":[55],"via":[56],"retrieval-augmented":[57,120],"generation":[58],"(RAG)":[59],"on":[60,130],"data":[62],"and":[63,116,119],"performs":[64],"supervised":[65],"fine-tuning":[66,118],"(SFT).Second,":[67],"propose":[69],"customized":[71],"direct":[72],"preference":[73],"optimization":[74],"(DPO)":[75],"approach":[76],"reinforce":[78],"behaviors":[81],"explicitly.Unlike":[82],"static":[83],"retrieval":[84],"methods,":[85,121],"dynamically":[87],"generates":[88],"tailored":[89],"references":[91],"during":[92],"inference,":[93],"effectively":[94],"mitigating":[95],"harmful":[96],"decision":[97],"shortcuts.Extensive":[98],"experiments":[99],"demonstrate":[100],"that":[101],"substantially":[103],"outperforms":[104],"state-of-the-art":[105],"(DeepSeek":[108],"R1,":[109],"QwQ),":[110],"specialized":[111],"(LLaMA":[114],"Guard),":[115],"advanced":[117],"achieving":[122],"an":[123],"average":[124],"F1":[125],"score":[126],"improvement":[127],"of":[128],"24.9%":[129],"challenging":[131],"benchmarks.":[134]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-07-02T00:00:00"}