Navigating the EU AI Act: A Practitioner’s Guide to Risk Classification
New research reveals the complexities of categorizing AI systems under Europe’s landmark regulations and proposes solutions for consistent compliance.
Science
The Ripple Effect of AI Risk
Current AI safety checks often overlook the complex ways components and stakeholders interact, potentially creating unforeseen and widespread problems.
Riding the Wave: How Information Cascades Shape Financial Markets
A new geometric framework reveals how financial markets respond to information avalanches, creating predictable pathways and opportunities for arbitrage.
The Rise of Autonomous Agents: Securing a Connected Future
As AI systems gain increasing autonomy and connect to form complex networks, a new era of security challenges demands urgent attention.
Riding the Waves: Smarter Risk Forecasting for Turbulent Markets
![During the 2008 global financial crisis, optimal window sizes for risk assessment dynamically adjusted alongside forecasts of Value at Risk [latex]VaR[/latex] and Expected Shortfall [latex]ES[/latex], demonstrating a responsive relationship between assessment parameters and evolving market conditions.](https://arxiv.org/html/2603.01157v1/2603.01157v1/x10.png)
A new adaptive window selection method improves financial risk predictions by dynamically adjusting to changing market conditions.
Networked Risk: Forecasting Volatility in Financial Systems
A new study reveals how accounting for connections between financial institutions dramatically improves the accuracy of volatility predictions.
Beyond the Hype: Deep Learning’s Edge in Financial Forecasting
![Performance comparisons reveal that across models, a 10% volatility rescaling of gross profit and loss ([latex] PnL [/latex]) consistently demonstrates discernible differences in performance metrics.](https://arxiv.org/html/2603.01820v1/2603.01820v1/Images/Gross_PnL.png)
A rigorous new benchmark reveals which deep learning architectures consistently deliver superior risk-adjusted returns in financial time series prediction.
Reading Between the Lines: AI Models Predict Suicide Risk by Simulating Online Dialogue
A new framework leverages multi-agent systems and causal reasoning to better identify individuals at risk of suicide based on their online conversations.
Seeing the Forest and the Trees: AI Predicts Patient Outcomes from Digital Pathology
A new approach leverages the power of graph neural networks to analyze whole-slide images and predict patient survival rates with improved accuracy.
Taming Lattice QCD with Machine Learning
![A hybrid gauge-fixing approach, leveraging trained parameters from the L21S2-1N-Z scheme, demonstrates comparable performance to a pure iterative baseline-achieving a normalized computational cost of 0.9753-while exhibiting consistent convergence, as evidenced by the evolution of the gauge-fixing functional [latex]F[g][/latex], relative differences [latex]\Delta F[g][/latex], and the diminishing count of incomplete configurations across numerous test configurations.](https://arxiv.org/html/2602.23731v1/2602.23731v1/x8.png)
A new approach leverages convolutional neural networks to significantly speed up the complex process of gauge fixing in lattice quantum chromodynamics.