·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
‘Odyssey’ director Christopher Nolan calls AI an obvious ‘Trojan horse’19m◆Nonprofit Current AI is racing to build the World Wide Web of AI, free for all1h◆Dave Eggers told OpenAI staff that ChatGPT was ‘silencing an entire generation’18h◆Kimi: Threat or menace?20h◆The apps, gadgets, and tools every reader needs1d◆Neil Rimer thinks the AI money is coming back out1d◆The Steering Budget: Examples beat Knobs1d◆Polestar: Drift-Aware Cache Calibration and Token Commitment for Efficient Inference of Diffusion LLMs1d◆RxBrain: Embodied Cognition Foundation Model with Joint Language-Visual Reasoning and Imagination1d◆HABIB_TAZ at SemEval-2026 Task 11: Disentangling Formal Logic from Content via Synthetic Training and Multi-Objective Optimization1d◆When a Verified World Model Still Loses: Play-Adequacy vs Prediction-Accuracy in LLM-Synthesized Code World Models1d◆SAGA: Schema-Aware Grounding for Agentic Text-to-SPARQL Generation1d◆ReasFlow: Assisting Reasoning-Centric Scientific Discovery in Applied Mathematics via a Knowledge-Based Multi-Agent System1d◆LBA: Textual Hard-Label Adversarial Attack under Low Query Budgets1d◆Eta Given Delta: Defining LLM Tool Efficiency With Marginal Tool Utility1d◆Simplicity Paradox: Debunking myths about prompting and datasets for LLM evaluation1d◆LIGO-PINN: Learned Initialization via Gated Optimization to Alleviate Convergence Failures in Physics Informed Neural Networks1d◆OmniaBench: Benchmarking General AI Agents Across Diverse Scenarios1d◆When AI Blurs the Boundaries of Contribution: An Empirical Study of Authorship Calibration1d◆Digital Pantheon: Simulating and Auditing Coalition Formation with LLM Agents1d◆‘Odyssey’ director Christopher Nolan calls AI an obvious ‘Trojan horse’19m◆Nonprofit Current AI is racing to build the World Wide Web of AI, free for all1h◆Dave Eggers told OpenAI staff that ChatGPT was ‘silencing an entire generation’18h◆Kimi: Threat or menace?20h◆The apps, gadgets, and tools every reader needs1d◆Neil Rimer thinks the AI money is coming back out1d◆The Steering Budget: Examples beat Knobs1d◆Polestar: Drift-Aware Cache Calibration and Token Commitment for Efficient Inference of Diffusion LLMs1d◆RxBrain: Embodied Cognition Foundation Model with Joint Language-Visual Reasoning and Imagination1d◆HABIB_TAZ at SemEval-2026 Task 11: Disentangling Formal Logic from Content via Synthetic Training and Multi-Objective Optimization1d◆When a Verified World Model Still Loses: Play-Adequacy vs Prediction-Accuracy in LLM-Synthesized Code World Models1d◆SAGA: Schema-Aware Grounding for Agentic Text-to-SPARQL Generation1d◆ReasFlow: Assisting Reasoning-Centric Scientific Discovery in Applied Mathematics via a Knowledge-Based Multi-Agent System1d◆LBA: Textual Hard-Label Adversarial Attack under Low Query Budgets1d◆Eta Given Delta: Defining LLM Tool Efficiency With Marginal Tool Utility1d◆Simplicity Paradox: Debunking myths about prompting and datasets for LLM evaluation1d◆LIGO-PINN: Learned Initialization via Gated Optimization to Alleviate Convergence Failures in Physics Informed Neural Networks1d◆OmniaBench: Benchmarking General AI Agents Across Diverse Scenarios1d◆When AI Blurs the Boundaries of Contribution: An Empirical Study of Authorship Calibration1d◆Digital Pantheon: Simulating and Auditing Coalition Formation with LLM Agents1d◆
News/Privacy Leakage in Federated Learning in Radiology Reports: A Comparative Evaluation of Tokenizer-Driven Privacy Risks
arxiv
PublishedJuly 18, 2026 at 4:00 AM
—neutral

Privacy Leakage in Federated Learning in Radiology Reports: A Comparative Evaluation of Tokenizer-Driven Privacy Risks

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

arXiv:2607.14205v1 Announce Type: new Abstract: Federated learning (FL) enables multi-institutional training on clinical text without sharing raw data, but gradient inversion can reconstruct sensitive information from shared model updates. The extent of this leakage for radiology reports, and the ro

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 →

No replies yet. Be first.

Source
↗
arxiv
Read original ↗All from arxiv →

Related coverage

More from ARXIV
arxivThe Steering Budget: Examples beat Knobs1darxivPolestar: Drift-Aware Cache Calibration and Token Commitment for Efficient Inference of Diffusion LLMs1darxivRxBrain: Embodied Cognition Foundation Model with Joint Language-Visual Reasoning and Imagination1darxivHABIB_TAZ at SemEval-2026 Task 11: Disentangling Formal Logic from Content via Synthetic Training and Multi-Objective Optimization1d
The Bubble Brief
WEEKLY

Read AI insights every Tuesday — top movers, new releases, story of the week.

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

Originally published on arxiv ↗
HomeModelsNews