GPUs, training clusters, MLOps, and deployment
I'm profoundly ambivalent re: how to feel about this; is it great -- what a scrappy, bold pivot! Or wildly dumb - its so far from their c...
Once a $4 billion apparel juggernaut, Allbirds will rebrand as NewBird AI, a “GPU-as-a-Service” company. Hey, if you can't beat ’em, join...
So, yesterday run was a success and I did get an avg rollout length of about 64 tokens as attached in the image! This was with quality_re...
![[2509.26335] TrackCore-F: Deploying Transformer-Based Subatomic Particle Tracking on FPGAs](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
The paper discusses TrackCore-F, a methodology for deploying Transformer-based models for subatomic particle tracking on FPGAs, highlight...
This paper presents FlexGT, a method for optimizing distributed stochastic problems by balancing communication and computation, achieving...
This paper presents a framework for formal reasoning about the confidence and robustness of neural networks, proposing a unified techniqu...
The paper presents a novel framework for batch speculative decoding, addressing critical failures in existing methods and achieving signi...
The paper introduces superposed parameterised quantum circuits, enhancing quantum machine learning by embedding multiple parameter sets i...
The paper presents Lorica, a novel framework aimed at enhancing personalized adversarial robustness in machine learning models, particula...
This article examines the relevance of statistical methods in the age of deep learning, using ordinary differential equation (ODE) invers...
This article presents EAPrivacy, a benchmark for evaluating the physical-world privacy awareness of large language models (LLMs), reveali...
VoiceBridge introduces a novel one-step latent bridge model for general speech restoration, enhancing audio quality from various distorti...
The paper introduces ReliabilityRAG, a framework designed to enhance the robustness of Retrieval-Augmented Generation (RAG) systems again...
The paper presents a novel method, gPerXAN, for Federated Domain Generalization (FedDG) that enhances model performance by effectively as...
The paper introduces Virne, a benchmarking framework designed for Reinforcement Learning-based resource allocation in Network Function Vi...
The paper discusses a novel approach to inference for relative sparsity in healthcare decision-making, addressing the need for uncertaint...
This paper presents a novel framework for predicting low-altitude network coverage using disentangled representation learning, addressing...
ExtractBench introduces a benchmark and evaluation framework for extracting structured data from unstructured documents like PDFs, addres...
This paper explores the non-identifiability of steering vectors in large language models (LLMs), revealing that these vectors cannot be u...
This paper introduces Accelerated Sequential Flow Matching, a Bayesian filtering framework that enhances real-time inference in stochasti...
This paper presents methods for distilling privileged information in language models, focusing on improving performance in multi-turn env...
This paper characterizes and optimizes KVCache, a caching mechanism for large language model (LLM) serving at a major cloud provider, hig...
This paper presents a novel algorithm for training resistive networks using Generalized Equilibrium Propagation, aiming to enhance energy...
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