GPUs, training clusters, MLOps, and deployment
Nvidia-backed Asia AI data center provider Firmus has now raised $1.35 billion in six months.
Anthropic launched Project Glasswing, a cybersecurity initiative in which it’s partnering with Nvidia, Apple, and others, and debuted a n...
I’ve been seeing more people talk about TeraBox lately, especially around storage for AI-related workflows. Curious if anyone here has us...
![[2602.18045] Conformal Tradeoffs: Guarantees Beyond Coverage](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
This article presents a framework for operational certification in conformal predictors, focusing on trade-offs beyond mere coverage, and...
The paper presents PenTiDef, a novel framework designed to enhance privacy and robustness in decentralized federated intrusion detection ...
The paper presents TierMem, a novel memory framework for agents that balances the need for accurate evidence with efficiency, reducing la...
This paper introduces a framework for sequence models using closed subgroups of U(d), deriving recurrent and transformer architectures fr...
This paper explores the unreliability of steering vectors in language models, examining how geometric predictors and linear approximation...
The paper presents FedZMG, a novel client-side optimization algorithm for Federated Learning that addresses client-drift issues without i...
The paper presents JPmHC, a framework enhancing deep learning stability by replacing identity skips in residual connections with a traina...
This paper explores the monitorability of chain-of-thought (CoT) systems in LLMs using information theory, identifying errors that affect...
GeneZip introduces a novel DNA compression model that optimizes genomic data representation by focusing on region-aware compression, achi...
This paper critiques the T-shirt sizing estimation method in AI projects, highlighting five key assumptions that often lead to failure an...
The paper introduces RAT+, a novel architecture that enhances attention mechanisms in machine learning by combining dense pretraining wit...
This article explores college students' experiences with generative AI in higher education, highlighting the pressures and social dynamic...
The paper presents SeedFlood, a novel approach for scalable decentralized training of large language models (LLMs) that minimizes communi...
The paper presents RGD-Blast, a deep surrogate model designed for accurate long-term blast wave prediction, addressing challenges in comp...
This paper explores model compression techniques for neural networks, focusing on projection geometry to improve accuracy and efficiency ...
The article discusses the implementation of a Cloud Run Hub for stabilizing Gemini Enterprise A2A interactions across multiple projects a...
This article explores asynchronous heavy-tailed optimization, addressing challenges in machine learning related to gradient noise and opt...
The paper explores the limitations of unsupervised learning methods, specifically Self-Organizing Maps (SOMs), in maintaining fairness by...
This paper presents APEMO, a novel runtime scheduling layer designed to enhance the reliability of long-horizon agentic systems by optimi...
This article explores the integration of formal domain ontologies into language models to enhance their reliability in mathematical reaso...
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