·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
Replit is no longer working with Anthropic, CEO says13h◆How Itaú is building generative AI for its entire customer base15h◆Roundtables: A Conversation With the Creator of AI-Designed Viruses16h◆India becomes the latest country to report rogue AI agent activity16h◆An Nvidia insider-turned-VC on why robotics hasn’t hit its ChatGPT moment, yet18h◆Physical AI is more than robots, says the Nvidia veteran now investing in it18h◆Elorian’s first AI model wants to reason with images, not just about them18h◆Jev is Vercel’s fastest-adopted AI model ever18h◆A week with RTX Spark: everything we’ve learned using Nvidia’s new laptops19h◆Mark Wahlberg on using AI in film ‘the right way’ and being open to an AI clone carrying on his legacy20h◆Meta’s new terms may allow it to train AI on news sites for free20h◆Veritas expands its anti-counterfeit chip to jewelry, trophies, and fragrance bottles20h◆Replit’s CEO says the future of work is the ‘self-driving company’21h◆Optimal Hydra: Model Heterogeneous Federated Learning for LLMs using Data-Informed Hydra-Nets1d◆Judging the Judges: Confidence and Disagreement in Rubrics as Rewards1d◆Content associations with answer selection and engagement in supply chain community question answering1d◆ORACLE-SWE: Quantifying the Contribution of Critical Information Signals on SWE Agents1d◆REKI: Registering Knowledge in VLAs1d◆Multimodal Remote Inference1d◆HyCo: Hybrid Drafting for Cost-Efficient Mobile-Cloud Speculative Decoding1d◆Replit is no longer working with Anthropic, CEO says13h◆How Itaú is building generative AI for its entire customer base15h◆Roundtables: A Conversation With the Creator of AI-Designed Viruses16h◆India becomes the latest country to report rogue AI agent activity16h◆An Nvidia insider-turned-VC on why robotics hasn’t hit its ChatGPT moment, yet18h◆Physical AI is more than robots, says the Nvidia veteran now investing in it18h◆Elorian’s first AI model wants to reason with images, not just about them18h◆Jev is Vercel’s fastest-adopted AI model ever18h◆A week with RTX Spark: everything we’ve learned using Nvidia’s new laptops19h◆Mark Wahlberg on using AI in film ‘the right way’ and being open to an AI clone carrying on his legacy20h◆Meta’s new terms may allow it to train AI on news sites for free20h◆Veritas expands its anti-counterfeit chip to jewelry, trophies, and fragrance bottles20h◆Replit’s CEO says the future of work is the ‘self-driving company’21h◆Optimal Hydra: Model Heterogeneous Federated Learning for LLMs using Data-Informed Hydra-Nets1d◆Judging the Judges: Confidence and Disagreement in Rubrics as Rewards1d◆Content associations with answer selection and engagement in supply chain community question answering1d◆ORACLE-SWE: Quantifying the Contribution of Critical Information Signals on SWE Agents1d◆REKI: Registering Knowledge in VLAs1d◆Multimodal Remote Inference1d◆HyCo: Hybrid Drafting for Cost-Efficient Mobile-Cloud Speculative Decoding1d◆
News/ERIS: Enhancing the Privacy-Utility-Scalability Trade-Off in Federated Learning via Federated Shard Aggregation
arxiv
PublishedOctober 12, 2026 at 4:00 AM

ERIS: Enhancing the Privacy-Utility-Scalability Trade-Off in Federated Learning via Federated Shard Aggregation

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

arXiv:2602.08617v3 Announce Type: replace Abstract: Scaling Federated Learning (FL) to billion-parameter models forces a challenging trade-off between privacy, scalability, and model utility. Existing solutions often tackle these challenges in isolation, sacrificing accuracy, relying on costly crypt

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 →

No replies yet. Be first.

Source
↗
arxiv
Read original ↗All from arxiv →

Related coverage

More from ARXIV
arxivOptimal Hydra: Model Heterogeneous Federated Learning for LLMs using Data-Informed Hydra-Nets1darxivJudging the Judges: Confidence and Disagreement in Rubrics as Rewards1darxivContent associations with answer selection and engagement in supply chain community question answering1darxivORACLE-SWE: Quantifying the Contribution of Critical Information Signals on SWE Agents1d
The Bubble Brief
MON · WED · FRI

Read AI 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