model-auditing
Behavioral auditing toolkit for LLMs — audit any model across 8 dimensions (factual, toxicity, bias, sycophancy, reasoning, refusal, deception, over-refusal) using teacher-forced confidence probes.
Subgroup-stratified, calibration-aware fairness auditing for ML models: DeLong AUC confidence intervals, per-subgroup calibration error, multiple-comparison-corrected significance, and a novel five-axis cross-platform protocol (CPFE). Grounded in peer-reviewed methods.
Compress LLMs while auditing whether they still know truth vs myths. SVD compression + false-belief detection in one toolkit.
