·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
A Nvidia insider-turned-VC on why robotics hasn’t hit its ChatGPT moment, yet1h◆Physical AI is more than robots, says the Nvidia veteran now investing in it1h◆Elorian’s first AI model wants to reason with images, not just about them1h◆Jev is Vercel’s fastest-adopted AI model ever2h◆A week with RTX Spark: everything we’ve learned using Nvidia’s new laptops2h◆Mark Wahlberg on using AI in film ‘the right way’ and being open to an AI clone carrying on his legacy3h◆Meta’s new terms may allow it to train AI on news sites for free3h◆Veritas expands its anti-counterfeit chip to jewelry, trophies, and fragrance bottles3h◆Replit’s CEO says the future of work is the ‘self-driving company’5h◆Optimal Hydra: Model Heterogeneous Federated Learning for LLMs using Data-Informed Hydra-Nets13h◆Judging the Judges: Confidence and Disagreement in Rubrics as Rewards13h◆Content associations with answer selection and engagement in supply chain community question answering13h◆ORACLE-SWE: Quantifying the Contribution of Critical Information Signals on SWE Agents13h◆REKI: Registering Knowledge in VLAs13h◆Multimodal Remote Inference13h◆Open Benchmark of AI Impact on Humans (ImpactBench): an expert-guided, open platform for the holistic evaluation of AI impact on humans13h◆Training Reasoning Models to Generate Diverse Scientific Ideas13h◆Linear Independence of Polynomial Compositions with Bounded Input Degree13h◆Kolab: Benchmarking Human-Agent Collaboration in Long-Horizon Workflows13h◆WorldCast: Exploring Intelligent Visual Generation in World State Prediction13h◆A Nvidia insider-turned-VC on why robotics hasn’t hit its ChatGPT moment, yet1h◆Physical AI is more than robots, says the Nvidia veteran now investing in it1h◆Elorian’s first AI model wants to reason with images, not just about them1h◆Jev is Vercel’s fastest-adopted AI model ever2h◆A week with RTX Spark: everything we’ve learned using Nvidia’s new laptops2h◆Mark Wahlberg on using AI in film ‘the right way’ and being open to an AI clone carrying on his legacy3h◆Meta’s new terms may allow it to train AI on news sites for free3h◆Veritas expands its anti-counterfeit chip to jewelry, trophies, and fragrance bottles3h◆Replit’s CEO says the future of work is the ‘self-driving company’5h◆Optimal Hydra: Model Heterogeneous Federated Learning for LLMs using Data-Informed Hydra-Nets13h◆Judging the Judges: Confidence and Disagreement in Rubrics as Rewards13h◆Content associations with answer selection and engagement in supply chain community question answering13h◆ORACLE-SWE: Quantifying the Contribution of Critical Information Signals on SWE Agents13h◆REKI: Registering Knowledge in VLAs13h◆Multimodal Remote Inference13h◆Open Benchmark of AI Impact on Humans (ImpactBench): an expert-guided, open platform for the holistic evaluation of AI impact on humans13h◆Training Reasoning Models to Generate Diverse Scientific Ideas13h◆Linear Independence of Polynomial Compositions with Bounded Input Degree13h◆Kolab: Benchmarking Human-Agent Collaboration in Long-Horizon Workflows13h◆WorldCast: Exploring Intelligent Visual Generation in World State Prediction13h◆
News/From raw data to neutrino candidates: a neural-network pipeline for Baikal-GVD
arxiv
PublishedMay 13, 2026 at 4:00 AM

From raw data to neutrino candidates: a neural-network pipeline for Baikal-GVD

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

arXiv:2605.11176v1 Announce Type: cross Abstract: We present a neural-network-based data processing pipeline for Baikal-GVD, designed to improve event reconstruction quality and accelerate neutrino candidates selection. The pipeline comprises three stages: fast suppression of extensive air shower ev

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-Nets13harxivJudging the Judges: Confidence and Disagreement in Rubrics as Rewards13harxivContent associations with answer selection and engagement in supply chain community question answering13harxivORACLE-SWE: Quantifying the Contribution of Critical Information Signals on SWE Agents13h
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