Finding the Moment: Smarter Image Search with Event-Based AI
A new approach to image retrieval focuses on identifying key events within images, allowing for more accurate searches based on complex natural language queries.
Science
The Price of Uncertainty: How Bubbles Form in Restricted Markets
![The emergence of bubbles hinges on a delicate balance - a sufficient excess of buoyant force overcoming the resisting forces of surface tension and gravity, a condition meticulously defined by [latex] \Delta P = \sigma \frac{1}{r} + \rho g h [/latex].](https://arxiv.org/html/2512.21115v1/bubble.png)
New research reveals how limitations on short selling, combined with uncertainty about market models, can drive the formation of asset price bubbles.
Mapping Meaning: How Embedding Geometry Reveals Protein Relationships
New research shows that the geometric properties of language model embeddings can expose underlying structure in protein sequences, offering a powerful way to assess representation quality.
Seeing Isn’t Always Understanding: Testing the Limits of Visual AI
A new benchmark reveals that even advanced vision-language models struggle with complex visual reasoning despite excelling at simpler image-text tasks.
Smarter Routes for Mobile Robots
A new metaheuristic framework significantly improves path planning for robots navigating complex, continuous environments.
Forecasting the Future: A Platform for Rigorous Time Series Evaluation
A new platform, TS-Arena, addresses the critical challenges of data leakage and reliable evaluation in the rapidly evolving field of time series forecasting.
Seeing Through the Synthetic: A New Approach to Detecting AI-Generated Images
Researchers are shifting focus from identifying telltale artifacts to modeling the inherent characteristics of real images for more reliable detection of AI-generated content.
Catching Quantum Rhythm: Synchronization in a Driven Oscillator
![The steady-state synchronization of a van der Pol oscillator, quantified by [latex]\delta[/latex], exhibits a complex relationship with damping and driving strength; strong phase-locking and collective dynamics ([latex]\delta >> 1[/latex]) emerge within specific parameter regimes, while weak or absent phase-locking ([latex]\delta > 1[/latex]) dominates outside these “tongues,” a behavior mirrored across classical and quantum systems-where increased driving force qualitatively enhances nonclassicality up to the quantum limit ([latex]\kappa_{2} = 1[/latex])-and ultimately converges towards synchronization patterns reminiscent of the classical case even in the deep quantum regime ([latex]\kappa_{2} >> 1[/latex]).](https://arxiv.org/html/2512.21272v1/Fig1c.jpg)
New research unveils a method for characterizing quantum synchronization in a fundamental nonlinear system, the Van der Pol oscillator, using advanced quantum measurement techniques.
Seeing the Unseen: AI Spots Anomalies in Complex MRI Scans
A new deep learning framework offers robust anomaly detection in multi-sequence MRI data, even when critical scan types are missing.
Can Simulated People Replace Real-World Testing for Algorithms?
A new study explores whether using AI to mimic human behavior can provide a reliable alternative to costly and complex field experiments for evaluating machine learning methods.