·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
An AI Security Agent for University ACMIS: Multi-Vector Threat Detection and Automated Response35m◆Navalia: Advancing Cowork Agents through Verifiable Task Synthesis and Long-Horizon Post-Training35m◆Large language model and reinforcement learning based autonomous construction and progress updates35m◆Pareto-Optimal RTL Code Generation via Multi-Objective Reinforcement Learning with Large Language Models35m◆MedPAO-Assist: Edge-Deployable, Modality-Aware Agentic AI for Radiology Report Structuring35m◆DataPraxis: Scaling Analytics Tasks via Verified Workspace Evolution35m◆Industrial Agentic AI: LLM-Driven New-Generation Agents for Smart Manufacturing35m◆Fix, Not Just Resample: Bounded Compiler-Guided Repair in Lean 435m◆MAMath-Bench: Process-Aware and Robust Evaluation of Multimodal Multi-Agent Mathematical Reasoning35m◆LightCRS: Lightweight Multi-Domain Conversational Recommendation System35m◆When Planning Problems Become Hard for LLMs: Separating Structural Complexity from Semantic Interpretability35m◆SPEM: Structure-Aware Procedural Memory for Efficient Skill Use in LLM Agents35m◆Does Multi-Agent Collaboration Reduce Hallucination in Clinical Tasks?35m◆Teaching AI Agent to Play Poker Strategically Through Preference Optimization35m◆M-Plan: Comprehensive Planning For LLM Agents with Memory Arrangement35m◆Physical AI: Concepts, Techniques, and Challenges35m◆ReuF2F: Benchmarking Coding Agents on Formalized Undergraduate Research Problems35m◆A general-purpose System One decision model for clinical records35m◆Omni-Woodpecker: Hallucination Correction via Evidence-Prior Rebalancing for Omni LLMs35m◆PROVISO: Provenance-Informed Action Selection for Secure LLM Agents35m◆An AI Security Agent for University ACMIS: Multi-Vector Threat Detection and Automated Response35m◆Navalia: Advancing Cowork Agents through Verifiable Task Synthesis and Long-Horizon Post-Training35m◆Large language model and reinforcement learning based autonomous construction and progress updates35m◆Pareto-Optimal RTL Code Generation via Multi-Objective Reinforcement Learning with Large Language Models35m◆MedPAO-Assist: Edge-Deployable, Modality-Aware Agentic AI for Radiology Report Structuring35m◆DataPraxis: Scaling Analytics Tasks via Verified Workspace Evolution35m◆Industrial Agentic AI: LLM-Driven New-Generation Agents for Smart Manufacturing35m◆Fix, Not Just Resample: Bounded Compiler-Guided Repair in Lean 435m◆MAMath-Bench: Process-Aware and Robust Evaluation of Multimodal Multi-Agent Mathematical Reasoning35m◆LightCRS: Lightweight Multi-Domain Conversational Recommendation System35m◆When Planning Problems Become Hard for LLMs: Separating Structural Complexity from Semantic Interpretability35m◆SPEM: Structure-Aware Procedural Memory for Efficient Skill Use in LLM Agents35m◆Does Multi-Agent Collaboration Reduce Hallucination in Clinical Tasks?35m◆Teaching AI Agent to Play Poker Strategically Through Preference Optimization35m◆M-Plan: Comprehensive Planning For LLM Agents with Memory Arrangement35m◆Physical AI: Concepts, Techniques, and Challenges35m◆ReuF2F: Benchmarking Coding Agents on Formalized Undergraduate Research Problems35m◆A general-purpose System One decision model for clinical records35m◆Omni-Woodpecker: Hallucination Correction via Evidence-Prior Rebalancing for Omni LLMs35m◆PROVISO: Provenance-Informed Action Selection for Secure LLM Agents35m◆
News/Adaptive Differential Privacy for Federated Medical Image Segmentation Across Diverse Modalities
arxiv
PublishedApril 10, 2026 at 4:00 AM
▲bullish

Adaptive Differential Privacy for Federated Medical Image Segmentation Across Diverse Modalities

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

arXiv:2604.06518v1 Announce Type: cross Abstract: Large volumes of medical data remain underutilized because centralizing distributed data is often infeasible due to strict privacy regulations and institutional constraints. In addition, models trained in centralized settings frequently fail to gener

Stay posted· Newsletter

Three short emails a week: Monday, Wednesday and Friday. Top movers, new models and the most-referenced story.

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

Your email is used only to send The Bubble Brief. Privacy policy

Discussion
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
03
#medical-imaging#federated-learning#privacy

No replies yet. Be first.

Source
↗
arxiv
Read original ↗All from arxiv →
Tags
03
#medical-imaging#federated-learning#privacy

Related coverage

More from ARXIV
arxivAn AI Security Agent for University ACMIS: Multi-Vector Threat Detection and Automated Response35marxivNavalia: Advancing Cowork Agents through Verifiable Task Synthesis and Long-Horizon Post-Training35marxivLarge language model and reinforcement learning based autonomous construction and progress updates35marxivPareto-Optimal RTL Code Generation via Multi-Objective Reinforcement Learning with Large Language Models35m
The Bubble Brief
MON · WED · FRI

Read medical-imaging insights every Monday, Wednesday and Friday — top movers, new models, story of the week.

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

Your email is used only to send The Bubble Brief. Privacy policy

Originally published on arxiv ↗
PrivacyTermsRefundsLegal notice|AboutMethodologyContact

© 2026 Databubble

Built by Marouane Gazouzi · Readyo, AI interview coach

HomeModelsNews