·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
GlobeBench: Evaluating Text-Based World Model Capabilities for Scalable Environment Simulations1h◆Algorithm Modelization: Transforming Optimization Algorithms into Evolvable Intelligence1h◆SimOPD: Relational Knowledge Transfer for On-Policy Distillation1h◆Generative Policy Improvement from Observational Data1h◆SkillBrowser: Selective Skill Exposure for Scalable Skill-Using Agents1h◆GEMS: Molecular Structure Elucidation as Learned Search over Isomer Graphs1h◆OwlSight: A Panoramic Monitor for Chain-of-Thought Reasoning1h◆Beyond Large Language Models: A Mental World Model Framework for Mental Modeling, Simulation, Evolution, and Interpretability1h◆Hard Instances on Demand1h◆ARBOR: Locating Reasoning Failures in Long Chains of Thought through Reasoning State Tracking1h◆Aligning Language Models Towards Counterfactual Invariance1h◆Language Models Learn to Improve Language Models1h◆TUPLE-Bench: Evaluating and Mitigating Privacy-Utility Trade-offs in Typed Decision Models1h◆STAIF: A Stage-wise Optimization for Complex Instruction Following1h◆Q-Reflector: Learning GUI Action Reflection with Generated Conditions1h◆When Should Agents Check External State? Budgeting Observations for Stored Intentions1h◆RIT-RAG: Navigating Document Corpora with Retrieval-Induced Trees1h◆MultiWorldBench: Do Independently Controlled Views Describe One Shared World?1h◆Are Multimodal Benchmarks Really Useful? Item-Level Multimodal Benchmark Diagnosis via Structure-Response Co-Calibration1h◆Understanding and Defending VLM Jailbreaks via Jailbreak-Related Representation Shift1h◆GlobeBench: Evaluating Text-Based World Model Capabilities for Scalable Environment Simulations1h◆Algorithm Modelization: Transforming Optimization Algorithms into Evolvable Intelligence1h◆SimOPD: Relational Knowledge Transfer for On-Policy Distillation1h◆Generative Policy Improvement from Observational Data1h◆SkillBrowser: Selective Skill Exposure for Scalable Skill-Using Agents1h◆GEMS: Molecular Structure Elucidation as Learned Search over Isomer Graphs1h◆OwlSight: A Panoramic Monitor for Chain-of-Thought Reasoning1h◆Beyond Large Language Models: A Mental World Model Framework for Mental Modeling, Simulation, Evolution, and Interpretability1h◆Hard Instances on Demand1h◆ARBOR: Locating Reasoning Failures in Long Chains of Thought through Reasoning State Tracking1h◆Aligning Language Models Towards Counterfactual Invariance1h◆Language Models Learn to Improve Language Models1h◆TUPLE-Bench: Evaluating and Mitigating Privacy-Utility Trade-offs in Typed Decision Models1h◆STAIF: A Stage-wise Optimization for Complex Instruction Following1h◆Q-Reflector: Learning GUI Action Reflection with Generated Conditions1h◆When Should Agents Check External State? Budgeting Observations for Stored Intentions1h◆RIT-RAG: Navigating Document Corpora with Retrieval-Induced Trees1h◆MultiWorldBench: Do Independently Controlled Views Describe One Shared World?1h◆Are Multimodal Benchmarks Really Useful? Item-Level Multimodal Benchmark Diagnosis via Structure-Response Co-Calibration1h◆Understanding and Defending VLM Jailbreaks via Jailbreak-Related Representation Shift1h◆
News/Timer-M1: A Multivariate Time Series Foundation Model via Learning Primitives
arxiv
PublishedOctober 9, 2026 at 4:00 AM

Timer-M1: A Multivariate Time Series Foundation Model via Learning Primitives

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

arXiv:2610.11734v1 Announce Type: cross Abstract: We introduce Timer-M1, a pretrained multivariate time series foundation model that learns with primitives for zero-shot forecasting. Across domains, time series share elementary temporal and relational patterns, termed primitives, yet differ in how t

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
arxivGlobeBench: Evaluating Text-Based World Model Capabilities for Scalable Environment Simulations1harxivAlgorithm Modelization: Transforming Optimization Algorithms into Evolvable Intelligence1harxivSimOPD: Relational Knowledge Transfer for On-Policy Distillation1harxivGenerative Policy Improvement from Observational Data1h
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