Fortifying Homomorphic Encryption Against Known-Plaintext Attacks
A new modification to the Fully Homomorphic Modified Rivest Scheme enhances security while preserving the ability to compute on encrypted data.
Science
Building Resilient AI: A New Loss Function for Error-Tolerant Neural Networks
A novel training approach enhances the robustness of quantized neural networks against bit errors, paving the way for more reliable deployment in resource-constrained environments.
AI Grading Gets a Reality Check
/|\text{Baseline}-\text{Human}|[/latex]- achieved by large language models on the ASAP-SAS dataset; a transformer ensemble (point A, Ormerod, 2022) and a fine-tuned GPT ensemble (point B, Ormerod & Kwako, 2024) progressively surpass earlier baselines-with a subsequent GPT-4 implementation (point C, Jiang & Bosch, 2024) projected to reach a normalized score of -1.52-indicating a substantial, ongoing refinement in automated assessment capabilities.](https://arxiv.org/html/2603.04820v1/2603.04820v1/x1.png)
A comprehensive analysis reveals that current artificial intelligence systems struggle to accurately assess short-answer responses, exposing fundamental limitations in their understanding of meaning.
Drone Hacking: 5G’s Hidden Weakness
New research reveals critical vulnerabilities in 5G Standalone networks that could allow attackers to compromise unmanned aerial vehicle (UAV) communications and control.
Chasing Ghosts in the Machine: Securing Collaborative AI Systems
As artificial intelligence increasingly relies on interconnected agents, detecting sophisticated attacks requires tracing the flow of information between them.
The Topology of Trust: Solving Elections in Anonymous Networks
![A quasi-covering, specifically the ball [latex]B_{\mathbf{D}_1}(v_1, r)[/latex], identifies regions within one graph ([latex]\mathbf{D}_1[/latex]) that exhibit local structural similarity to another graph ([latex]\mathbf{D}_0[/latex]), effectively demonstrating the existence of substantial areas sharing a common local appearance.](https://arxiv.org/html/2603.05118v1/2603.05118v1/x1.png)
New research reveals how understanding network structure can unlock reliable leader election even when identities are hidden and randomness is shared.
Beyond the Horizon: When Black Holes Lose Their Identity
![The study delineates the domain of existence for solutions induced by curvature, quantifying deviations from the Kerr solution-characterized by dimensionless spin and coupling parameter [latex] -\alpha/M^{2} [/latex]-through measurable properties including horizon area [latex] A_{s} [/latex], Hawking temperature [latex] T_{s} [/latex], entropy [latex] S_{s} [/latex], and scalar charge [latex] Q_{s} [/latex].](https://arxiv.org/html/2603.05064v1/2603.05064v1/charge.png)
New research demonstrates that black holes aren’t always defined by just mass and spin, revealing multiple stable configurations arising from a complex interplay of gravity and scalar fields.
Counting to Complexity: Analyzing Reachability in Counter Automata
A new analysis defines the limits of determining reachable states in vector addition systems with integer counters, offering insights into the inherent computational difficulty of these systems.
Smarter Federated Learning: Balancing Security, Accuracy, and Speed
A new approach interleaves privacy-enhancing techniques to optimize the delicate trade-off between data protection, model quality, and computational cost in distributed machine learning.
Unwinding Quantum Change: How Symmetry Reveals Dynamical Transitions
 = (0.5, -1)[/latex] to either [latex](\mu, \Delta) = (1.5, 1)[/latex] or [latex](0.8, 1)[/latex] - exhibit distinct behaviors dependent on the number of modes satisfying the condition [latex]\cos(2\delta\theta_{k_c}) = 0[/latex]; specifically, the resulting dynamical mode energy [latex]\tilde{\lambda}_{k_n}(t)[/latex] at time [latex]t_c[/latex] varies with the parameter [latex]m_2[/latex], highlighting a nuanced relationship between quench protocols, mode excitation, and system energy.](https://arxiv.org/html/2603.05284v1/2603.05284v1/x2.png)
New research clarifies the behavior of quantum systems undergoing rapid change by tracking how their internal symmetries evolve over time.