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