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...
Dell and HIVE have partnered to deploy Nvidia’s next-generation AI chips, though further details about the collaboration are not available.
Policy: - budget = 1000 - each `provision_gpu(a100)` call = 500 Result: - call 1 -> ALLOW - call 2 -> ALLOW - call 3 -> DENY (`B...
![[2511.04681] Dark Energy Survey Year 3 results: Simulation-based $w$CDM inference from weak lensing and galaxy clustering maps with deep learning: Analysis design](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
This article presents a novel simulation-based inference pipeline utilizing deep learning to analyze weak lensing and galaxy clustering m...
This article presents the GEneral Synthetic-Powered Inference (GESPI) framework, which enhances statistical inference by integrating synt...
VIRENA is a novel platform designed for controlled experimentation in social media environments, enabling researchers to study human-AI i...
The Protean Compiler introduces an agile framework for fine-grain phase ordering in compilers, enhancing LLVM's capabilities with machine...
The paper explores strategic hiring in labor markets dominated by algorithmic evaluation, highlighting the inefficiencies of naive hiring...
This article presents a refined Bayesian optimization framework for efficient beam alignment in intelligent indoor wireless environments,...
The paper presents a novel approach to reduce the computational complexity of Neural Tangent Kernel (NTK) methods through dataset distill...
The paper presents Quant VideoGen, a framework for autoregressive long video generation that addresses the limitations of KV cache memory...
This article investigates the integration and management of pre-trained models (PTMs) in open-source software projects, introducing the c...
The paper presents StableQAT, a novel framework for quantization-aware training (QAT) that enhances stability and efficiency at ultra-low...
This article presents a novel approach to inverting non-injective functions using Twin Neural Network Regression, focusing on locally inv...
This paper presents a novel framework for out-of-distribution (OOD) detection in molecular complexes using diffusion models tailored for ...
This paper presents novel frameworks for communication compression in distributed learning, addressing bandwidth constraints in federated...
The paper presents A2G, a novel framework for adaptive aggregation in quantum federated learning, addressing performance issues due to cl...
The paper presents FreqPolicy, a novel flow-based visuomotor policy that enhances efficiency in robotic manipulation by imposing frequenc...
This paper evaluates backdoor attacks against federated learning model adaptation, focusing on the impact of Low-Rank Adaptation (LoRA) o...
The paper introduces VerifyBench, a new benchmarking framework for evaluating reference-based reward systems in large language models, hi...
The paper introduces Q3R, a novel Quadratic Reweighted Rank Regularizer designed to enhance low-rank training in deep learning models, ac...
The paper presents FindAnything, a framework for open-vocabulary and object-centric mapping that enhances robot exploration in unknown en...
This article presents the Uncertain Safety Critic (USC), a novel approach to enhance safety in reinforcement learning (RL) by balancing s...
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