model auditing

Decomposing Direct and Indirect Biases in Linear Models Under Demographic Parity Constraint AAAI 2026 Differences That Matter: Auditing Models for Capability Gap Discovery and Rectification CVPR 2026 DoTA: Latent Distribution Conditioned Data Attribution for Diffusion Models WACV 2026 FailureAtlas: Mapping the Failure Landscape of T2I Models via Active Exploration CVPR 2026 Make Mechanistic Interpretability Auditable: A Call to Develop Guidelines via Continuous Collaborative Reviewing ACL 2026 Active Fourier Auditor for Estimating Distributional Properties of ML Models AAAI 2025 An Auditing Test to Detect Behavioral Shift in Language Models ICLR 2025 Auditing and Enforcing Conditional Fairness via Optimal Transport AAAI 2025 POW: Political Overton Windows of Large Language Models EMNLP 2025 TFDP: Token-Efficient Disparity Audits for Autoregressive LLMs via Single-Token Masked Evaluation EMNLP 2025 The “r” in “woman” stands for rights. Auditing LLMs in Uncovering Social Dynamics in Implicit Misogyny EMNLP 2025 Visualizing token importance for black-box language models AISTATS 2025 Causal Analysis for Robust Interpretability of Neural Networks WACV 2024 FairBelief - Assessing Harmful Beliefs in Language Models NAACL 2024 Membership Inference Attacks against Large Vision-Language Models NeurIPS 2024 PANORAMIA: Privacy Auditing of Machine Learning Models without Retraining NeurIPS 2024 Automatically Auditing Large Language Models via Discrete Optimization ICML 2023 Cross-GAN Auditing: Unsupervised Identification of Attribute Level Similarities and Differences Between Pretrained Generative Models CVPR 2023 Tools for Verifying Neural Models' Training Data NeurIPS 2023 How Faithful is your Synthetic Data? Sample-level Metrics for Evaluating and Auditing Generative Models ICML 2022 On the Epistemic Limits of Personalized Prediction NeurIPS 2022 Auditing Black-Box Prediction Models for Data Minimization Compliance NeurIPS 2021 Learning to Deceive with Attention-Based Explanations ACL 2020 Can You Trust This Prediction? Auditing Pointwise Reliability After Learning AISTATS 2019 Disentangling Influence: Using disentangled representations to audit model predictions NeurIPS 2019