![The study demonstrates a unifying framework for iterative feedback processes, revealing that diverse approaches - from acoustic experiments to advanced generative models like CycleGAN and diffusion models - collectively exhibit the dynamics of a Markov process, where successive model generations are linked by a transformation operator [latex]T(\cdot)[/latex] acting on the current image distribution [latex]X_n[/latex].](https://arxiv.org/html/2602.19033v1/x19.png)
New research reveals that iterative feedback loops in image generation create a resonant state, explaining why these models sometimes get stuck and offering clues to unlock their full potential.
A new network analysis reveals the complex web of connections driving volatility and spillover effects among Chinese real estate firms during the ongoing crisis.
The convergence of artificial intelligence, modeling & simulation, and digital twins is unlocking unprecedented capabilities for system understanding and predictive optimization.
A new framework combines explainable AI with strategic data handling to significantly improve the accuracy and transparency of cybersecurity threat detection.
As large language models become increasingly integrated into autonomous AI agents, ensuring their security requires a fundamental shift towards proactive supply chain oversight.
Researchers have developed a novel diagnostic framework leveraging random matrix theory to assess the underlying quality of crash classification models, moving beyond simple accuracy metrics.
A new framework evaluates the potential for AI-powered mental health support systems to provide unsafe or ineffective care, revealing critical vulnerabilities.
New research reveals that the architecture of stablecoins fundamentally shapes how systemic risk spreads during periods of market turbulence.
A new study explores whether large language models can effectively translate the complex logic behind credit risk predictions into human-understandable explanations.
A new framework and benchmark suite aim to ensure financial large language models are reliable, transparent, and ready for real-world deployment.