Researchers have demonstrated a clear violation of Bell’s inequality within the framework of relativistic quantum field theory, solidifying the foundations of non-local quantum mechanics.
Researchers have developed a novel framework for modeling complex relationships in time series data by focusing on quantile dynamics and ensuring stable, interpretable results.
A new hybrid architecture balances on-chain security with off-chain efficiency to unlock high-frequency trading of energy and carbon assets.
As defenses against side-channel and speculative attacks grow more complex, ensuring their seamless integration is critical to maintaining system security.
![Memory capacity benchmarks reveal that the Memory-Hierarchical Network (MHN) maintains perfect recall up to a pattern density of [latex]P=N[/latex], significantly exceeding the performance of the Phasor-graph memory-which falls below 95% recall near the classical Hopfield bound of [latex]0.138N[/latex]-and demonstrating a substantial advantage over the Echo State Network, which rapidly degrades in associative recall performance due to its architectural limitations.](https://arxiv.org/html/2601.04362v1/x8.png)
A new approach to reinforcement learning uses the principles of brain rhythms and sleep-like stages to enable agents to learn complex tasks and improve generalization.
New research details a powerful defense against prompt injection attacks, leveraging synthetic data and enhanced reasoning capabilities to protect large language models.
New research explores a powerful mathematical technique for calculating knot invariants and gaining insights into their asymptotic behavior.
Researchers have developed a new computational suite to model the complex interiors and dynamics of rapidly rotating neutron stars with unprecedented accuracy.
![The research demonstrates a performance trade-off, assessed via an R-D curve on the Bicycle scene from the MipNeRF360 dataset, wherein varying [latex]\lambda_{ssim}[/latex] values-ranging from 0.1 to 0.4-influences the method’s results when benchmarked against PCGS and GoDE.](https://arxiv.org/html/2601.04348v1/images/R-D_Curve.png)
Researchers have developed a progressive codec that leverages spatial context and residual quantization to enable efficient streaming of high-quality 3D Gaussian Splatting scenes.
New research demonstrates how to subtly dismantle techniques used to identify the origins of large language model outputs, potentially undermining intellectual property protections.