·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
Neil Rimer thinks the AI money is coming back out6h◆The Steering Budget: Examples beat Knobs6h◆Polestar: Drift-Aware Cache Calibration and Token Commitment for Efficient Inference of Diffusion LLMs6h◆RxBrain: Embodied Cognition Foundation Model with Joint Language-Visual Reasoning and Imagination6h◆When a Verified World Model Still Loses: Play-Adequacy vs Prediction-Accuracy in LLM-Synthesized Code World Models6h◆SAGA: Schema-Aware Grounding for Agentic Text-to-SPARQL Generation6h◆ReasFlow: Assisting Reasoning-Centric Scientific Discovery in Applied Mathematics via a Knowledge-Based Multi-Agent System6h◆LBA: Textual Hard-Label Adversarial Attack under Low Query Budgets6h◆Eta Given Delta: Defining LLM Tool Efficiency With Marginal Tool Utility6h◆Simplicity Paradox: Debunking myths about prompting and datasets for LLM evaluation6h◆LIGO-PINN: Learned Initialization via Gated Optimization to Alleviate Convergence Failures in Physics Informed Neural Networks6h◆OmniaBench: Benchmarking General AI Agents Across Diverse Scenarios6h◆When AI Blurs the Boundaries of Contribution: An Empirical Study of Authorship Calibration6h◆Digital Pantheon: Simulating and Auditing Coalition Formation with LLM Agents6h◆Inoculation Adapters: Improved Selective Generalization of Capabilities with Fewer Surprising Backdoors6h◆Large Audio Language Models for Spoofing-Aware Speaker Verification6h◆ANet Patu-1: The Value of Connection in the Agent Network6h◆Automatically Evolving Prompt Guidelines for Task-Specific Optimization6h◆MAPS: Modeling Co-Existing Subjective Perspectives and Shared Meaning in Multi-Agent Cognitive Dialogue6h◆Automatic Hard Example Synthesis with Multi-Level Agentic Data Curation6h◆Neil Rimer thinks the AI money is coming back out6h◆The Steering Budget: Examples beat Knobs6h◆Polestar: Drift-Aware Cache Calibration and Token Commitment for Efficient Inference of Diffusion LLMs6h◆RxBrain: Embodied Cognition Foundation Model with Joint Language-Visual Reasoning and Imagination6h◆When a Verified World Model Still Loses: Play-Adequacy vs Prediction-Accuracy in LLM-Synthesized Code World Models6h◆SAGA: Schema-Aware Grounding for Agentic Text-to-SPARQL Generation6h◆ReasFlow: Assisting Reasoning-Centric Scientific Discovery in Applied Mathematics via a Knowledge-Based Multi-Agent System6h◆LBA: Textual Hard-Label Adversarial Attack under Low Query Budgets6h◆Eta Given Delta: Defining LLM Tool Efficiency With Marginal Tool Utility6h◆Simplicity Paradox: Debunking myths about prompting and datasets for LLM evaluation6h◆LIGO-PINN: Learned Initialization via Gated Optimization to Alleviate Convergence Failures in Physics Informed Neural Networks6h◆OmniaBench: Benchmarking General AI Agents Across Diverse Scenarios6h◆When AI Blurs the Boundaries of Contribution: An Empirical Study of Authorship Calibration6h◆Digital Pantheon: Simulating and Auditing Coalition Formation with LLM Agents6h◆Inoculation Adapters: Improved Selective Generalization of Capabilities with Fewer Surprising Backdoors6h◆Large Audio Language Models for Spoofing-Aware Speaker Verification6h◆ANet Patu-1: The Value of Connection in the Agent Network6h◆Automatically Evolving Prompt Guidelines for Task-Specific Optimization6h◆MAPS: Modeling Co-Existing Subjective Perspectives and Shared Meaning in Multi-Agent Cognitive Dialogue6h◆Automatic Hard Example Synthesis with Multi-Level Agentic Data Curation6h◆
News/QwenPaw-Data: Bridging Facts, Methodology, and Execution for Autonomous Enterprise Data Analytics
arxiv
PublishedJuly 15, 2026 at 4:00 AM

QwenPaw-Data: Bridging Facts, Methodology, and Execution for Autonomous Enterprise Data Analytics

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

arXiv:2607.11019v2 Announce Type: replace Abstract: Enterprise data analysis is emerging as a distinct frontier for autonomous agents. Compared with general-purpose interaction and software engineering, it operates in an open, ambiguous, and continuously evolving environment. These characteristics c

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
arxivThe Steering Budget: Examples beat Knobs6harxivPolestar: Drift-Aware Cache Calibration and Token Commitment for Efficient Inference of Diffusion LLMs6harxivRxBrain: Embodied Cognition Foundation Model with Joint Language-Visual Reasoning and Imagination6harxivWhen a Verified World Model Still Loses: Play-Adequacy vs Prediction-Accuracy in LLM-Synthesized Code World Models6h
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