New research shows that large language models, combined with a clever data retrieval technique, can accurately forecast which startups are likely to thrive, even with limited information.
As complex tasks are increasingly delegated to teams of AI agents, understanding and addressing the reasons for their failures is critical for building dependable systems.
New research reveals how safety mechanisms are encoded within large language models and demonstrates a method to pinpoint and manipulate the specific components responsible for preventing harmful outputs.
A new analysis of waveform data reveals a pattern of low-magnitude earthquakes in the Kamchatka Peninsula leading up to a significant seismic event.
![The Fission-GRPO framework operates through iterative refinement-initially optimizing a policy [latex]\pi_{\theta}[/latex] across a query distribution [latex]\mathcal{D}[/latex], then isolating error trajectories via a diagnostic simulator [latex]\mathcal{S}_{\phi}[/latex], and finally employing a multiplicative resampling process-governed by a factor [latex]G^{\prime}[/latex]-to steer the policy toward successful recovery paths, embodying a system designed not to prevent decay, but to adaptively reconfigure itself within it.](https://arxiv.org/html/2601.15625v1/x2.png)
New research demonstrates a method for improving the reliability of AI agents by transforming failed actions into valuable learning opportunities.
A new approach to modeling spiking neural networks using hypergraphs promises to dramatically improve how these networks are deployed on specialized neuromorphic hardware.
This industry case study details a practical and secure approach to deploying AI-powered chatbots for small businesses using distributed, cloud-native technologies.
A new machine vision system, built using a custom convolutional neural network, is showing promise in the early detection of skin lesions.
![As semantic density increases-measured by ρ-neural accuracy rapidly declines, evidenced by a sharp decrease in N50N\_{50}, which validates the Orthogonality Constraint by demonstrating that higher densities lead to increased key overlap and subsequent interference; achieving values below [latex]\rho < 0.3[/latex] proved unattainable with realistic fact structures.](https://arxiv.org/html/2601.15313v1/fig_density_vs_collapse.png)
New research reveals a fundamental constraint on how neural networks store information, explaining why they falter when faced with complex, overlapping memories.
A new framework uses artificial intelligence to predict and mitigate risks in live streaming by analyzing patterns of behavior across multiple sessions.