·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
AI researchers stranded Claude on a virtual desert island. It started to “play.”3h◆RCPN: towards robust pseudo-labels in unsupervised CLIP adaptation via consistent prototypes and neighborhoods8h◆Can Graph Learning Learn Circuits?8h◆Beyond Fixed Acquisition Functions: Temporal Difference Active Learning for Perturbation Discovery8h◆Trajectory-Guided Steering: Mitigating Spurious Feature Bias in Clinical Classification8h◆Sentence-Level Topic Modeling with Lexical and Contextual Evidence8h◆Referring Multi-Object Tracking with Diverse Dynamic Expressions8h◆R$^2$ Flow: Recursive Self-Improvement via Recursive Skill Evolution8h◆Logic-Guided Graph Denoising Diffusion Models8h◆Unit-level aggregation breaks coverage in causal foundation models8h◆Mask-Based Deep Symbolic Regression8h◆RECREG: Recovery-based Shielding for Regular Safety Properties in Reinforcement Learning8h◆FormInv: A Measurement Protocol for Semantic Invariance in Mathematical Reasoning Benchmarks8h◆Every Model Cheats: Prompt-Level Mitigation of Cheating on Offensive Cyber Tasks8h◆EduWild: How Teacher-Configured Chatbots Fail in Real-World Use and How to Fix Them8h◆Recognizing Study Lineage Is Not Enough: Over-Crediting Same-Trial Evidence in LLM-Based Medical Verification8h◆Paved with True Intents: Intent-Aware Training Improves LLM Safety Classification Across Training Regimes8h◆Diagnosing GNN Failure Modes with Layer-Wise Probe Entropy8h◆CastClaw: A Human-in-the-Loop Autonomous Agent for Interactive Time Series Forecasting8h◆Transferability of Learned States in Neural PDE Solvers8h◆AI researchers stranded Claude on a virtual desert island. It started to “play.”3h◆RCPN: towards robust pseudo-labels in unsupervised CLIP adaptation via consistent prototypes and neighborhoods8h◆Can Graph Learning Learn Circuits?8h◆Beyond Fixed Acquisition Functions: Temporal Difference Active Learning for Perturbation Discovery8h◆Trajectory-Guided Steering: Mitigating Spurious Feature Bias in Clinical Classification8h◆Sentence-Level Topic Modeling with Lexical and Contextual Evidence8h◆Referring Multi-Object Tracking with Diverse Dynamic Expressions8h◆R$^2$ Flow: Recursive Self-Improvement via Recursive Skill Evolution8h◆Logic-Guided Graph Denoising Diffusion Models8h◆Unit-level aggregation breaks coverage in causal foundation models8h◆Mask-Based Deep Symbolic Regression8h◆RECREG: Recovery-based Shielding for Regular Safety Properties in Reinforcement Learning8h◆FormInv: A Measurement Protocol for Semantic Invariance in Mathematical Reasoning Benchmarks8h◆Every Model Cheats: Prompt-Level Mitigation of Cheating on Offensive Cyber Tasks8h◆EduWild: How Teacher-Configured Chatbots Fail in Real-World Use and How to Fix Them8h◆Recognizing Study Lineage Is Not Enough: Over-Crediting Same-Trial Evidence in LLM-Based Medical Verification8h◆Paved with True Intents: Intent-Aware Training Improves LLM Safety Classification Across Training Regimes8h◆Diagnosing GNN Failure Modes with Layer-Wise Probe Entropy8h◆CastClaw: A Human-in-the-Loop Autonomous Agent for Interactive Time Series Forecasting8h◆Transferability of Learned States in Neural PDE Solvers8h◆
News/An Autonomous AI Security Agent for Banking: Multi-Vector Fraud and AML Detection Across Retail and Corporate Accounts
arxiv
PublishedOctober 9, 2026 at 4:00 AM

An Autonomous AI Security Agent for Banking: Multi-Vector Fraud and AML Detection Across Retail and Corporate Accounts

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

arXiv:2606.17555v4 Announce Type: replace-cross Abstract: Banks face two threat families with fundamentally different detection requirements: signature-based fraud (card-not-present attacks, account takeover, ATM cloning) and behavioural financial crime (structuring, layering, mule networks, busines

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
arxivRCPN: towards robust pseudo-labels in unsupervised CLIP adaptation via consistent prototypes and neighborhoods8harxivCan Graph Learning Learn Circuits?8harxivBeyond Fixed Acquisition Functions: Temporal Difference Active Learning for Perturbation Discovery8harxivTrajectory-Guided Steering: Mitigating Spurious Feature Bias in Clinical Classification8h
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