NeurIPS 2024 Past Tabular & structured data
NeurIPS 2024 Workshop on Regulatable ML
RegML 2024
- Submission deadline
- Sep 13, 2024, 11:59 UTC imported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Auto-imported from the OpenReview venue record on 2026-06-10 — please verify and enrich (topics are keyword-guessed).
Accepted papers (44)
Fetched from OpenReview (v2) on 2026-06-10.
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A Black-Box Watermarking Modulation for Semantic Segmentation Models
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A False Sense of Privacy: Evaluating Textual Data Sanitization Beyond Surface-level Privacy Leakage
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Active Fourier Auditor for Estimating Distributional Properties of ML Models
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AI-Generated Content and Public Persuasion: The Limited Effect of AI Authorship Labels
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An Autonomy-Based Classification: Liability in the Age of AI Agents
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Compliance Cards: Automated EU AI Act Compliance Analyses amidst a Complex AI Supply Chain
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CopyBench: Measuring Literal and Non-Literal Reproduction of Copyright-Protected Text in Language Model Generation
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Declare and Justify: Explicit assumptions in AI evaluations are necessary for effective regulation
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Examining Data Compartmentalization for AI Governance
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Exploiting Interpretable Capabilities with Concept-Enhanced Diffusion and Prototype Networks
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Fairness Implications of Machine Unlearning: Bias Risks in Removing NSFW Content from Text-to-Image Models
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FairProof : Confidential and Certifiable Fairness for Neural Networks
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Feature Responsiveness Scores: Model-Agnostic Explanations for Recourse
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Foundation Models and the EU AI Act
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Fundamental Limits in the Search for Less Discriminatory Algorithms—and How to Avoid Them
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Generative AI regulation can learn from social media regulation
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GPAI Evaluations Standards Taskforce: towards effective AI governance
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Homogeneous Algorithms Can Reduce Competition in Personalized Pricing
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How Many Van Goghs Does It Take to Van Gogh? Finding the Imitation Threshold
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IDs for AI Systems
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Influence-based Attributions can be Manipulated
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Integration of Generative AI in the Digital Markets Act: Contestability and Fairness from a Cross-Disciplinary Perspective
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Knowledge Distillation-Based Model Extraction Attack using GAN-based Private Counterfactual Explanations
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LLM-Generated Black-box Explanations Can Be Adversarially Helpful
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Mitigating Bias in Facial Recognition Systems: Centroid Fairness Loss Optimization
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Multilingual Compliance: A Comparative Study of Privacy Policies in Chinese, Japanese, and Korean
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Non-Interactive and Publicly Verifiable Zero-Knowledge Proof for Fair Decision Trees
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Optimal Selection Using Algorithmic Rankings with Side Information
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Policy Trees for Prediction: Interpretable and Adaptive Model Selection for Machine Learning
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Position: Challenges and Opportunities for Differential Privacy in the U.S. Federal Government
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Position: Participatory Assessment of Large Language Model Applications in an Academic Medical Center
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Powering LLM Regulation through Data: Bridging the Gap from Compute Thresholds to Customer Experiences
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Promoting User Data Autonomy During the Dissolution of a Monopolistic Firm
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Public Procurement for Responsible AI? Understanding U.S. Cities' Practices and Needs
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Quantifying Variance in Evaluation Benchmarks
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Regulation of Algorithmic Collusion, Refined: Testing Worst-case Calibrated Regret
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Responsible Artificial Intelligence (RAI) in US Federal Government : Principles, Policies, and Practices.
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Robustness and Cybersecurity in the EU Artificial Intelligence Act
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The Data Minimization Principle in Machine Learning
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Towards Data Governance of Frontier AI Models
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Towards Safe Multilingual Frontier AI
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Verification methods for international AI agreements
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vTune: Verification of fine-tuning through backdooring
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Weak-to-Strong Confidence Prediction