·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
AI has a water problem. Google thinks it has a fix3h◆Google must let publishers opt out of AI Search features, rules UK4h◆FederatedSkill: Federated Learning for Agentic Skill Evolution8h◆Toward a Modular Architecture for Embedded AI Agent Systems at the Edge8h◆A Graph Foundation Model with Spectral Parsing and Prototype-Guided Spatial Propagation8h◆Anomalies in Multivariate Time Series Benchmarks Are Mostly Univariate8h◆Evaluating the Reversal Curse in Model Editing8h◆Fast Unlearning at Scale via Margin Self-Correction8h◆Can Local Learning Match Self-Supervised Backpropagation?8h◆CAPER: Clause-Aligned Process Supervision for Text-to-SQL8h◆An Asymptotic Theory of Chain-of-Thought in In-Context Learning8h◆DeskCraft: Benchmarking Desktop Agents on Professional Workflows and Human-in-the-Loop Collaboration8h◆Enhanced Renewable Energy Forecasting using Context-Aware Conformal Prediction8h◆Don't Gamble, GAMBLe: An Analytical Framework for AI-Driven Research Systems8h◆RMPrior: Bridging Propagation Priors and Diffusion Refinement for Efficient Radio Map Construction8h◆Learning to Solve, Forgetting to Retain: Correct-Set Turnover in RLVR8h◆RogueMerge: Robust and Unified Attacks against LLM Model Merging8h◆The Road Ahead in Autonomous Driving: The KITScenes Multimodal Dataset8h◆MLSkip: Data Skipping for ML Filters via Lightweight Metadata8h◆Multi-Segment Attention: Enabling Efficient KV-Cache Management for Faster Large Language Model Serving8h◆AI has a water problem. Google thinks it has a fix3h◆Google must let publishers opt out of AI Search features, rules UK4h◆FederatedSkill: Federated Learning for Agentic Skill Evolution8h◆Toward a Modular Architecture for Embedded AI Agent Systems at the Edge8h◆A Graph Foundation Model with Spectral Parsing and Prototype-Guided Spatial Propagation8h◆Anomalies in Multivariate Time Series Benchmarks Are Mostly Univariate8h◆Evaluating the Reversal Curse in Model Editing8h◆Fast Unlearning at Scale via Margin Self-Correction8h◆Can Local Learning Match Self-Supervised Backpropagation?8h◆CAPER: Clause-Aligned Process Supervision for Text-to-SQL8h◆An Asymptotic Theory of Chain-of-Thought in In-Context Learning8h◆DeskCraft: Benchmarking Desktop Agents on Professional Workflows and Human-in-the-Loop Collaboration8h◆Enhanced Renewable Energy Forecasting using Context-Aware Conformal Prediction8h◆Don't Gamble, GAMBLe: An Analytical Framework for AI-Driven Research Systems8h◆RMPrior: Bridging Propagation Priors and Diffusion Refinement for Efficient Radio Map Construction8h◆Learning to Solve, Forgetting to Retain: Correct-Set Turnover in RLVR8h◆RogueMerge: Robust and Unified Attacks against LLM Model Merging8h◆The Road Ahead in Autonomous Driving: The KITScenes Multimodal Dataset8h◆MLSkip: Data Skipping for ML Filters via Lightweight Metadata8h◆Multi-Segment Attention: Enabling Efficient KV-Cache Management for Faster Large Language Model Serving8h◆
News/SMI: Statistical Membership Inference for Reliable Unlearned Model Auditing
arxiv
PublishedMay 8, 2026 at 4:00 AM
—neutral

SMI: Statistical Membership Inference for Reliable Unlearned Model Auditing

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2602.01150v2 Announce Type: replace-cross Abstract: Machine unlearning (MU) is essential for enforcing the right to be forgotten in machine learning systems. A key challenge of MU is how to reliably audit whether a model has truly forgotten specified training data. Membership Inference Attacks

Stay posted· Newsletter

A 5-min weekly brief — top movers, price watch, story of the week.

// no spam · unsubscribe one-click · free forever

Discussion
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#machine-learning#unlearning#auditing#security

No replies yet. Be first.

Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#machine-learning#unlearning#auditing#security

Related coverage

More from ARXIV
arxivFederatedSkill: Federated Learning for Agentic Skill Evolution8harxivToward a Modular Architecture for Embedded AI Agent Systems at the Edge8harxivA Graph Foundation Model with Spectral Parsing and Prototype-Guided Spatial Propagation8harxivAnomalies in Multivariate Time Series Benchmarks Are Mostly Univariate8h
The Bubble Brief
WEEKLY

Read machine-learning insights every Tuesday — top movers, new releases, story of the week.

// no spam · unsubscribe one-click · free forever

Originally published on arxiv ↗
HomeModelsNews