·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
Calibration-First Reward-Component Auditing for Reinforcement Learning Control in Smart Greenhouses1h◆LP Mining with LP2Graph: A Use Case for Railway Rescheduling1h◆Designing Agent-Ready Websites for AI Web Agents: A Framework for Machine Readability, Actionability, and Decision Reliability1h◆Graph Feedback Controls Consensus and Clique Formation in Open-Weight Language-Model Populations1h◆Operationalising Multi-Dimensional Evaluation for Conversational Agents: A Scalable, Governed Pipeline with Selective Re-evaluation and Model Benchmarking1h◆Connected by Construction: Learning Tractable Near-Tour Marginals for Traveling Salesman Problems1h◆Good Benchmarks1h◆On-Device Deep Research at 4B: Exposure Bounds Faithfulness, Retrieval Bounds Coverage1h◆How Many Tasks Are Enough for Agent Benchmark Decisions? A Replay Analysis of Public LLM Agent Benchmarks1h◆PM-Bench: Evaluating Prospective Memory in LLM Agents1h◆Isolation as a First-Class Principle for LLM-Agent System Safety: Concepts, Taxonomy, Challenges and Future Directions1h◆Accepted Prefixes Are Not All You Need: A Negative Result on PEFT-Based Block-Diffusion Drafting1h◆EVOQUANT: Self-Evolving Verifier-Guided Strategy Optimization for Robust Quantitative Trading1h◆Do We Really Need Transformers for Global Spatial Information Extraction in Traffic Forecasting?1h◆Function-Aware Fill-in-the-Middle as Mid-Training for Coding Agent Foundation Models1h◆The Model Knows Your Project, Not You: Measuring Recognition in LLMs with NameRank1h◆Evidence-Grounded AI for Musculoskeletal Care1h◆Vertical Standardisation for High-Risk AI Systems under the EU AI Act: A Domain-Specific Framework for Algorithmic Hiring1h◆Agentic Service-Oriented Computing: A Manifesto for the Next Frontier of Service-Oriented Computing1h◆Atomic Units of X: The Compression Layer of Intelligence1h◆Calibration-First Reward-Component Auditing for Reinforcement Learning Control in Smart Greenhouses1h◆LP Mining with LP2Graph: A Use Case for Railway Rescheduling1h◆Designing Agent-Ready Websites for AI Web Agents: A Framework for Machine Readability, Actionability, and Decision Reliability1h◆Graph Feedback Controls Consensus and Clique Formation in Open-Weight Language-Model Populations1h◆Operationalising Multi-Dimensional Evaluation for Conversational Agents: A Scalable, Governed Pipeline with Selective Re-evaluation and Model Benchmarking1h◆Connected by Construction: Learning Tractable Near-Tour Marginals for Traveling Salesman Problems1h◆Good Benchmarks1h◆On-Device Deep Research at 4B: Exposure Bounds Faithfulness, Retrieval Bounds Coverage1h◆How Many Tasks Are Enough for Agent Benchmark Decisions? A Replay Analysis of Public LLM Agent Benchmarks1h◆PM-Bench: Evaluating Prospective Memory in LLM Agents1h◆Isolation as a First-Class Principle for LLM-Agent System Safety: Concepts, Taxonomy, Challenges and Future Directions1h◆Accepted Prefixes Are Not All You Need: A Negative Result on PEFT-Based Block-Diffusion Drafting1h◆EVOQUANT: Self-Evolving Verifier-Guided Strategy Optimization for Robust Quantitative Trading1h◆Do We Really Need Transformers for Global Spatial Information Extraction in Traffic Forecasting?1h◆Function-Aware Fill-in-the-Middle as Mid-Training for Coding Agent Foundation Models1h◆The Model Knows Your Project, Not You: Measuring Recognition in LLMs with NameRank1h◆Evidence-Grounded AI for Musculoskeletal Care1h◆Vertical Standardisation for High-Risk AI Systems under the EU AI Act: A Domain-Specific Framework for Algorithmic Hiring1h◆Agentic Service-Oriented Computing: A Manifesto for the Next Frontier of Service-Oriented Computing1h◆Atomic Units of X: The Compression Layer of Intelligence1h◆
News/Traceable Fault Diagnosis for Battery Energy Storage Systems via Retrieval-Augmented Multi-Agent O&M Assistant
arxiv
PublishedJuly 3, 2026 at 4:00 AM
—neutral

Traceable Fault Diagnosis for Battery Energy Storage Systems via Retrieval-Augmented Multi-Agent O&M Assistant

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

arXiv:2607.01992v1 Announce Type: new Abstract: Large-scale battery energy storage systems (BESSs) require O&M decisions that combine alarms, cell-level measurements, device topology, diagnostic tables, historical cases, and maintenance documents. Monitoring platforms can flag threshold violations,

Stay posted· Newsletter

A 5-min weekly brief — top movers, price watch, story of the week.

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

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
arxivCalibration-First Reward-Component Auditing for Reinforcement Learning Control in Smart Greenhouses1harxivLP Mining with LP2Graph: A Use Case for Railway Rescheduling1harxivDesigning Agent-Ready Websites for AI Web Agents: A Framework for Machine Readability, Actionability, and Decision Reliability1harxivGraph Feedback Controls Consensus and Clique Formation in Open-Weight Language-Model Populations1h
The Bubble Brief
WEEKLY

Read AI insights every Tuesday — top movers, new releases, story of the week.

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

Originally published on arxiv ↗
HomeModelsNews