When Collaboration Goes Wrong: The Hidden Risks of AI Teams

As more complex tasks are delegated to groups of AI agents, understanding how errors spread and amplify within these systems becomes critical.

As more complex tasks are delegated to groups of AI agents, understanding how errors spread and amplify within these systems becomes critical.

New research reveals that popular evaluations of artificial intelligence safety have limited academic impact, raising questions about how we measure progress in this crucial field.
New research pushes the boundaries of computable structure theory, demonstrating conditions for constructing computable models of theories extending Peano Arithmetic.

A new benchmark assesses the ability of artificial intelligence agents to identify, fix, and exploit vulnerabilities within smart contracts.
![The renormalization-group flow of bond decimations-examined for a disordered spin chain of length 80 with long-range interactions parameterized by [latex]\alpha = 2.0[/latex]-reveals how a standard decimation procedure and a graph neural network-assisted approach each navigate the complex landscape of bond severances, with the probability of removing bonds of a given length-binned logarithmically-shifting predictably across renormalization group steps and averaged over numerous disorder configurations.](https://arxiv.org/html/2603.05164v1/2603.05164v1/rg_flow_heatmap.png)
Researchers have successfully employed machine learning to predict the entanglement properties of complex, disordered quantum systems, offering a new path to understanding their behavior.
A new system allows multiple AI agents to maintain context and respond faster by storing key information directly on device, rather than relying solely on short-term prompts.

This review explores how restricting the tools of propositional and modal logic impacts what we can express, and how easily we can reason with those limited systems.

Researchers are leveraging the power of quantum computers and spin chain models to explore the behavior of confining strings in quantum chromodynamics at extremely strong coupling.
New research reveals that intentionally miscalibrating noise levels during the decoding process can surprisingly enhance the performance of quantum LDPC codes.
A new protocol aims to safeguard financial transactions against the looming threat of quantum computing by combining advanced cryptography and privacy-enhancing technologies.