Sensing Mental Wellbeing: A New Era of Forecasting
Research reveals how data from our smartphones, combined with advanced artificial intelligence, can predict changes in mental health with increasing accuracy.
Science
Unraveling Language Model Collapse
![The study demonstrates that compounding data and weight recursion-where each generation of synthetic text refines training from the previous generation’s weights-results in measurable drift, quantified as the change in [latex]\Delta U_{\mathrm{LLN,cov}}(\delta)[/latex] and [latex]\Delta G_{\mathrm{KF}}(\delta)[/latex], relative to a baseline checkpoint.](https://arxiv.org/html/2601.03385v1/x2.png)
New research offers a powerful framework for understanding and predicting when large language models begin to lose coherence during prolonged, synthetic data training.
The Tipping Point of Finance: How Network Structure Drives Systemic Risk
New research reveals that financial networks exhibit surprisingly fragile stability, with even modest increases in interconnectedness potentially triggering cascading defaults.
China’s AI Economy: A Battle for Capital and Labor
New research models the dynamic interplay between artificial intelligence, physical capital, and the workforce in China, revealing both opportunities and risks for sustainable growth.
AI’s Shifting Sands: How US, EU, and China Define the Risks
A new comparative analysis reveals fundamentally different approaches to AI governance across the globe, driven by divergent institutional priorities and understandings of ‘AI safety’.
Mapping Financial Contagion: A New Network Approach
Researchers have developed a method to pinpoint the key transmission channels of risk within complex financial systems by analyzing how shocks propagate through the network.
Intelligent Wireless: The Rise of Foundation Models
A new wave of AI is transforming wireless networks, leveraging powerful foundation models to predict behavior and optimize performance.
Stellar Sounds: AI Decodes the Hearts of Stars
A new machine learning approach rapidly and accurately determines stellar properties by analyzing their natural vibrations, opening doors to more precise models of stellar evolution.
Predictive Policing for Machines: Detecting Industrial IoT Failures Before They Happen
![The comparative analysis of anomaly detection methods-tested against the KDDCup99, IoTID20, and WUSTL-IIoT datasets-demonstrates that performance, as measured by the Area Under the Curve [latex] AUC [/latex], fluctuates with the volume of records processed, highlighting the critical need for drift adaptation in maintaining reliable anomaly identification across evolving data streams.](https://arxiv.org/html/2601.03085v1/Figures/WUSTL.png)
A new method leverages machine learning to proactively identify anomalies in real-time data streams from industrial IoT devices, minimizing downtime and maximizing efficiency.
AI Takes the Network: A New Era for Connectivity
Generative artificial intelligence is rapidly transforming network design and operation, promising enhanced efficiency and adaptability.