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Verdict stability in fairness audits can swing dramatically, but VFR-Audit quantifies this uncertainty, revealing how bias-mitigation strategies impact reliability.
Even without architectural modifications, a new gradient inversion attack, ARES, can reconstruct high-fidelity training samples in federated learning, exposing a significant privacy risk.
