{"data":{"id":"1a788fd4-0586-4ed9-ac6e-0f271f581094","title":"CIRCUS: A Causal Intervention-Based Framework for Enhancing Counterfactual Fairness in Trained Classifiers","summary":"The paper presents CIRCUS, a causal intervention framework for improving counterfactual fairness in trained classifiers, built on a new generator called CITGAN. CIRCUS generates counterfactually discriminatory samples via causal intervention, then applies bias correction to their labels and retrains the classifier. On a DNN, the MMD_L and MMD_K values fell by averages of 39.7% and 40.4% versus the second-best result; for ResNet, the reductions were 56.7% and 54.5%.","solution":"The mitigation is the CIRCUS framework itself: generating counterfactually discriminatory samples through causal intervention, applying bias correction preprocessing to their labels, and retraining the classifier.","labels":["research","safety"],"sourceUrl":"http://ieeexplore.ieee.org/document/11435129","publishedAt":"2026-03-16T13:24:25.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":[],"issueType":"research","affectedPackages":null,"affectedPackageNames":null,"affectedPackageRefs":null,"affectedVendors":[],"affectedVendorsRaw":[],"classifierModel":"claude-haiku-5-5","classifierPromptVersion":"v4","summaryPromptVersion":"v2","headline":null,"headlinePromptVersion":null,"cvssVector":null,"attackVector":null,"attackComplexity":null,"privilegesRequired":null,"userInteraction":null,"exploitMaturity":null,"epssScore":null,"epssCheckedAt":null,"kevDateAdded":null,"advisoryAliases":null,"affectedPackagesSource":null,"affectedPackagesCheckedAt":null,"patchAvailable":null,"disclosureDate":"2026-03-16T13:24:25.000Z","fixReleasedAt":null,"daysToFix":null,"fixCheckedAt":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":null,"aiComponentTargeted":"model","llmSpecific":false,"classifierConfidence":0.85,"researchCategory":"peer_reviewed","atlasIds":null}}