UMKC Announces New Master of Science in Artificial Intelligence
UMKC announces a new Master of Science in Artificial Intelligence program aimed at addressing workforce demand for AI expertise, set to l...
GPUs, training clusters, MLOps, and deployment
UMKC announces a new Master of Science in Artificial Intelligence program aimed at addressing workforce demand for AI expertise, set to l...
Perplexity just ran a structural analysis on the criticism campaign against my work. What it found: synchronized language across posts, n...
Crescendo (Russinovich et al., USENIX Security 2025) is a multi-turn jailbreak that starts with innocent questions and gradually steers a...
The paper introduces MARS, a Modular Agent designed for automated AI research, emphasizing cost-aware planning and reflective memory to e...
This paper presents a theoretical framework establishing a Fano-style accuracy upper bound for single-pass reasoning in multi-hop questio...
The paper presents learning-based approaches to dynamic targeting for Earth observation satellites, demonstrating improved scientific dat...
MultiSHAP introduces a Shapley-based framework for explaining interactions in multimodal AI models, enhancing interpretability and trustw...
This paper presents a novel method for simulation-based inference that is robust to outliers and simplifies computation by eliminating th...
OpenAgentSafety introduces a modular framework for evaluating AI agent safety in real-world tasks, addressing critical vulnerabilities in...
Grappa introduces a gradient-only communication framework for scalable training of Graph Neural Networks (GNNs), improving speed and accu...
FlowSteer introduces an end-to-end reinforcement learning framework for automating workflow orchestration, addressing challenges like man...
This article presents CARL-XRay, a novel continual learning framework for chest radiograph classification that adapts to new datasets wit...
The paper introduces mini-vec2vec, an efficient method for aligning text embedding spaces using linear transformations, significantly imp...
The paper presents a novel approach, Bridge, for parallel scaling in LLM inference that generates interdependent responses, enhancing acc...
This paper explores vulnerabilities in diffusion language models (DLMs) related to priming attacks and proposes a novel safety alignment ...
This article introduces quantum agnostic learning protocols for depth-3 circuits, showcasing a quantum agnostic boosting method that enha...
The paper presents LSMART, an open-source simulator for evaluating Multi-Agent Path Finding (MAPF) algorithms in Automated Guided Vehicle...
The paper presents a novel framework, A LoD of Gaussians, for ultra-large-scale scene reconstruction and rendering using Gaussian splatti...
This paper presents EnergyUCB, a novel online GPU energy optimization method using a multi-armed bandit approach to balance performance a...
The paper presents a novel approach to Text-to-SQL systems by introducing dynamic workflows that adapt during inference, enhancing perfor...
This paper presents a non-intrusive data-driven model order reduction method for circuits using Hammerstein architectures, demonstrating ...
The paper introduces VLM-DEWM, a novel cognitive architecture designed to enhance vision-language planning in manufacturing by addressing...
The paper presents Horizon Imagination (HI), an innovative on-policy imagination process for reinforcement learning using diffusion-based...
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