·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
Meta releases its first frontier model, Muse Wonder9h◆WindBorne wins a hefty US Air Force contract for its balloon data9h◆Meta has some Wonder Full new AI models10h◆Honeyjar offers AI tools to improve PR and comms at every company11h◆Microsoft president says UK is best placed to drive AI regulation11h◆This AI startup says it can generate permit-ready blueprints in minutes11h◆TechCrunch Disrupt 2026 starts tomorrow: Your final chance to secure up to $100 ticket savings13h◆Microsoft’s new AI chip makes it less reliant on Nvidia’s GPUs14h◆Former Plaud exec raises $26M for AI app that listens to you in the background14h◆SmolWAM: A Latent World-Action Model for Robotic Manipulation on Edge Devices23h◆VETR: Execution-Grounded Self-Improving Agent for Symbolic Graphics Reasoning23h◆AI-Based On-Board Maritime Object Detection for Earth Observation Payload Data Reduction on Versal Embedded Hardware23h◆SEEDS: Preview-Guided Evidence Admission for Search Agents23h◆OccludeBench: Can VLMs Find What's Missing?23h◆Towards Easier-to-Tune Training Algorithms: New Results from AlgoPerf23h◆StereoEngine: Scaling Stereo Bimanual Robot Data without Stereo Cameras23h◆Dissecting Representation Structure in Vision Transformers: A Rigorous Architectural Study23h◆Surfing the Activation Wave: Analyzing the Information and Geometry of LLM Hidden States for Speculative Decoding23h◆Forecasting Corpus-Sampling Disagreement in Masked Text Reconstruction23h◆Probabilistic Calibration Is a Trainable Capability in Language Models23h◆Meta releases its first frontier model, Muse Wonder9h◆WindBorne wins a hefty US Air Force contract for its balloon data9h◆Meta has some Wonder Full new AI models10h◆Honeyjar offers AI tools to improve PR and comms at every company11h◆Microsoft president says UK is best placed to drive AI regulation11h◆This AI startup says it can generate permit-ready blueprints in minutes11h◆TechCrunch Disrupt 2026 starts tomorrow: Your final chance to secure up to $100 ticket savings13h◆Microsoft’s new AI chip makes it less reliant on Nvidia’s GPUs14h◆Former Plaud exec raises $26M for AI app that listens to you in the background14h◆SmolWAM: A Latent World-Action Model for Robotic Manipulation on Edge Devices23h◆VETR: Execution-Grounded Self-Improving Agent for Symbolic Graphics Reasoning23h◆AI-Based On-Board Maritime Object Detection for Earth Observation Payload Data Reduction on Versal Embedded Hardware23h◆SEEDS: Preview-Guided Evidence Admission for Search Agents23h◆OccludeBench: Can VLMs Find What's Missing?23h◆Towards Easier-to-Tune Training Algorithms: New Results from AlgoPerf23h◆StereoEngine: Scaling Stereo Bimanual Robot Data without Stereo Cameras23h◆Dissecting Representation Structure in Vision Transformers: A Rigorous Architectural Study23h◆Surfing the Activation Wave: Analyzing the Information and Geometry of LLM Hidden States for Speculative Decoding23h◆Forecasting Corpus-Sampling Disagreement in Masked Text Reconstruction23h◆Probabilistic Calibration Is a Trainable Capability in Language Models23h◆
News/IntSeqBERT: Learning Arithmetic Structure in OEIS via Modulo-Spectrum Embeddings
arxiv
PublishedJune 15, 2026 at 4:00 AM
—neutral

IntSeqBERT: Learning Arithmetic Structure in OEIS via Modulo-Spectrum Embeddings

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

arXiv:2603.05556v2 Announce Type: replace Abstract: Integer sequences in the OEIS span values from single-digit constants to astronomical factorials and exponentials, making prediction challenging for standard tokenised models that cannot handle out-of-vocabulary values or exploit periodic arithmeti

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
arxivSmolWAM: A Latent World-Action Model for Robotic Manipulation on Edge Devices23harxivVETR: Execution-Grounded Self-Improving Agent for Symbolic Graphics Reasoning23harxivAI-Based On-Board Maritime Object Detection for Earth Observation Payload Data Reduction on Versal Embedded Hardware23harxivSEEDS: Preview-Guided Evidence Admission for Search Agents23h
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