NeurIPS 2025 Past Tabular & structured data
NeurIPS 2025 Workshop on Regulatable ML
RegML 2025
- Submission deadline
- Aug 30, 2025, 23:59 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 (53)
Fetched from OpenReview (v2) on 2026-06-10.
-
(When) Should We Delegate AI Governance to AIs? Some Lessons from Administrative Law
-
A Framework for the Categorisation of General-Purpose AI Models under the EU AI Act
-
AgentCrypt: Advancing Privacy and (Secure) Computation in AI Agent Collaboration
-
AI, Climate, and Transparency: Operationalizing and Improving the AI Act
-
Anatomy of a Machine Learning Ecosystem: 2 Million Models on Hugging Face
-
Are You Getting What You Pay For? Auditing Model Substitution in LLM APIs
-
Auditable AI Literacy Interventions: Embedding Regulatory Principles into Higher Education
-
Beware! The AI Act Can Also Apply to Your AI Research Practices
-
Check Yourself Before You Wreck Yourself: Selectively Quitting Improves LLM Agent Safety
-
Cost Efficient Fairness Audit Under Partial Feedback
-
Data Forging Attacks on Cryptographic Model Certification
-
Debugging Concept Bottleneck Models through Removal and Retraining
-
Deepfakes in Political Manipulation: Evaluating Risks Under the AI Act
-
Differentially Private Adaptation of Diffusion Models via Noisy Aggregated Embeddings
-
Do AI Companies Make Good on Voluntary Commitments to the White House?
-
Emergency Response Measures for Catastrophic Risk
-
Empirical Evidence for Alignment Faking in a Small LLM and Prompt-Based Mitigation Techniques
-
ENCORE: Entropy-guided Reward Composition for Multi-head Safety Reward Models
-
EU-Agent-Bench: Measuring Illegal Behavior of LLM Agents Under EU Law
-
Examining the Vulnerability of Multi-Agent Medical Systems to Human Interventions for Clinical Reasoning
-
Explanation-Driven Counterfactual Testing for Faithfulness in Vision-Language Model Explanations
-
From Proposals to Enactment: The Procedural Bottleneck in AI Safety Regulation
-
Harmful Information Management Practices in Frontier AI Development
-
HashMark: Watermarking Tabular/Synthetic Data For Machine Learning Via Cryptographic Hash Functions
-
How Data-Related AI Research can Support Technical Solutions for Regulatory Compliance
-
How do data owners say no? A case study of data consent mechanisms in web-scraped vision-language AI training datasets
-
Inducing Uncertainty on Open-Weight Models for Test-Time Privacy in Image Recognition
-
Interpreting and Steering LLMs with Mutual Information-based Explanations on Sparse Autoencoders
-
It's complicated. The relationship of algorithmic fairness and non-discrimination regulations for high-risk systems in the EU AI Act
-
LatentGuard: Controllable Latent Steering for Robust Refusal of Attacks and Reliable Response Generation
-
Local Differences, Global Lessons: Insights from Organisation Policies for Legislation
-
MaskSQL: Safeguarding Privacy for LLM-Based Text-to-SQL via Abstraction
-
Military AI Cyber Agents (MAICAs) Constitute a Global Threat to Critical Infrastructure
-
On the Regulatory Potential of User Interfaces for AI Agent Governance
-
PersonaTeaming: Exploring How Introducing Personas Can Improve Automated AI Red-Teaming
-
Perspective: Lessons from Cybersecurity for Biological AI Safety and Regulation
-
Policy-as-Prompt: Turning AI Governance Rules into Guardrails for AI Agents
-
Position: Bridge the Gaps between Machine Unlearning and AI Regulation
-
Refining Inverse Constitutional AI for Dataset Validation under the EU AI Act
-
Regulating the Agency of LLM-based Agents
-
Scratchpad Thinking: Alternation Between Storage and Computation in Latent Reasoning Models
-
SemScore: Practical Explainable AI through Quantitative Methods to Measure Semantic Spuriosity
-
SPEAR++: Scaling Gradient Inversion via Sparsely-Used Dictionary Learning
-
SpecEval: Evaluating Model Adherence to Behavior Specifications
-
Specifying Computational Compliance for AI: Blueprint for a New Research Domain
-
Statutory Construction and Interpretation for Artificial Intelligence
-
StealthEval: A Probe-Rewrite-Evaluate Workflow for Reliable Benchmarks
-
The Backfiring Effect of Weak AI Safety Regulation
-
The Contribution of XAI for the Safe Development and Certification of AI: An Expert-Based Analysis
-
The Hidden Cost of Modeling $P(X)$: Membership Inference Attacks in Generative Text Classifiers
-
The Model Openness Framework: Promoting Completeness and Openness for Reproducibility, Transparency, and Usability in Artificial Intelligence
-
The Right to be Forgotten in Pruning: Unveil Machine Unlearning on Sparse Models
-
ValueDCG: Framework for Investigating Human Value Understanding Ability of Language Models through Discriminator-Critique Gap