Search: “hardware”

arXiv:2604.26413v1 Announce Type: cross Abstract: This paper presents Quantum Gatekeeper, a context-bound image steganography framework where successful payload recovery depends on both cryptographic

arXiv:2602.10718v3 Announce Type: replace-cross Abstract: While FP8 attention has shown substantial promise in innovations like FlashAttention-3, its integration into the decoding phase of the DeepSee

arXiv:2604.20891v1 Announce Type: cross Abstract: Memristive crossbars store numerical weights needing aggregation and decoding; a single junction means nothing alone. This paper presents a fundamenta

arXiv:2604.18837v1 Announce Type: cross Abstract: Quantum kernel methods have been proposed as a promising approach for leveraging near-term quantum computers for supervised learning, yet rigorous ben

Models like Qwen3 and Llama 3.2 are commonly used for n8n RAG workflows , with selection depending on use case requirements. Running Ollama models locally requires at least 16 GB of RAM on your device

arXiv:2604.11512v1 Announce Type: cross Abstract: The growing demand for deploying Small Language Models (SLMs) on edge devices, including laptops, smartphones, and embedded platforms, has exposed fun

IC-LoRA (In-Context LoRA) enables conditioning video generation on reference video frames at inference time, allowing fine-grained video-to-video control on top of a text-to-video base model. Unlike t

arXiv:2604.08780v1 Announce Type: cross Abstract: World models promise a paradigm shift in robotics, where an agent learns the underlying physics of its environment once to enable efficient planning a

arXiv:2610.12182v1 Announce Type: cross Abstract: Very-high-resolution Earth-observation satellites acquire more data than they can store and downlink, while in maritime surveillance the vessels cover

arXiv:2610.10037v1 Announce Type: new Abstract: Physical reservoir computing exploits the nonlinear dynamics of physical systems to process time-dependent data with greater energy efficiency than conv

arXiv:2610.03616v1 Announce Type: new Abstract: We present a generalized implementation of Look-Back and Look-Ahead Adaptive Model Predictive Control (LLA-MPC), a learning-free framework for real-time

arXiv:2610.02510v1 Announce Type: new Abstract: Campus AI tutors based on retrieval-augmented generation (RAG) must ground answers in assigned course materials while keeping textbooks and student dial

I've been wanting to test out LLM inference on FPGAs for a while now, but didn't have a big reason too since there were no frontier class models at 9B-27B scale (3.6 27B was great still but it didn't

Reupload: I'm adding this again, since previous post had a totally stupid title which made people assume this app is some kind of cloud/proprietary models UI - this is totally not the case here. In ve

arXiv:2609.36301v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) layers are central to frontier language models, and recent architectures push toward more and smaller experts. In this regime

Early this year when I was first looking at building up my inference capability you could get the 16GB Tesla P100s for between 60 and 80. Asked claude about it, told me absolutely not worth it. No ten

arXiv:2609.26067v1 Announce Type: new Abstract: Kolmogorov--Arnold Networks (KANs) replace scalar edge weights with learnable univariate functions, increasing flexibility but also parameter memory bec

arXiv:2609.22124v1 Announce Type: new Abstract: This paper describes the system submitted to the UNLP 2026 Shared Task on Multi-Domain Document Understanding. The challenge required extracting precise

arXiv:2609.23385v1 Announce Type: cross Abstract: Data acquisition (DAQ) systems at future particle physics experiments stand to benefit from the extremes of AI/ML development: large-scale foundation

arXiv:2609.17562v1 Announce Type: cross Abstract: Hybrid Spiking Neural Network (SNN)-Artificial Neural Network (ANN) architectures combine the energy efficiency of SNNs with the superior detection ac

arXiv:2609.08307v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as backends for intelligent web services, but serving them across the edge continuum requires balan

arXiv:2609.07199v1 Announce Type: new Abstract: Trust-Hub reuses host circuits: several files differ mainly in the inserted Trojan. When gates from sibling variants enter both training and test folds,

Its chat template has this line: {%- set resolved_reasoning_effort = reasoning_effort|default('xhigh') %} xhigh is the most expensive of its three settings (low / medium / xhigh). If you never set one

arXiv:2609.04705v1 Announce Type: cross Abstract: Passive cooling eliminates the energy overhead and mechanical failure modes of fans, making it attractive for edge deployment, yet sustained Deep Neur

Github link: https://github.com/thatblend/LLMPSP I wanted to see what the PSP can theoretically handle and I got my answer - a 90M model is about the max it can do without atrocious inference speeds.

arXiv:2609.02186v1 Announce Type: cross Abstract: Quantum generative models offer a promising framework for exploring whether quantum computation can enhance generative machine learning. Flow matching

Years ago I built a server, shelved it after some time, but recently realized I have it sitting there. I'm looking to pop in a Tesla V100 32GB card (with proper cooling). But are the component too old

I’m working on performance regression detection using machine learning/anomaly detection. My setup is basically: Healthy runs are used to learn normal behaviour Regression runs are used to see whether

arXiv:2608.08081v1 Announce Type: cross Abstract: Large mixture-of-experts (MoE) language models with 26--120 billion parameters exceed the memory capacity of consumer devices through three simultaneo

Hi everyone, I'm a systems analysis student researching a problem a lot of you probably know well: how much you actually trust the published VRAM/RAM requirements for open-source models before trying

arXiv:2608.03649v1 Announce Type: new Abstract: Fewer visual tokens do not guarantee lower end-to-end latency. We evaluate break-even with a reproducible protocol that accounts for decision overhead,

I let Gemma4-31b run on my laptop for like almost a day using a heavily altered pi to do a deep dive on our beloved Llama tangentially related Subreddit, and this was the conclusion. Feels pretty accu

arXiv:2504.03772v3 Announce Type: replace-cross Abstract: Respiratory diseases account for a significant portion of global mortality. Affordable and early detection is an effective way of addressing t

arXiv:2607.20162v1 Announce Type: new Abstract: The growing demand for intelligent processing at the edge of IoT networks is constrained by the severe computational and memory limitations of microcont

arXiv:2607.14021v1 Announce Type: new Abstract: Dexterous manipulation remains a critical bottleneck in industrial automation; tasks such as cable routing, connector insertion, and precision assembly

arXiv:2607.13897v1 Announce Type: new Abstract: The broadcast nature of wireless channels exposes radio-frequency (RF) networks to anomalous and malicious transmissions, making anomaly detection a fun

arXiv:2607.06915v1 Announce Type: new Abstract: Scaling down the resolution of input images can greatly reduce the computational overhead of convolutional neural networks (CNNs), which is promising fo

arXiv:2607.02753v1 Announce Type: cross Abstract: Neuromorphic controllers for size, weight, and power-constrained systems require neural architectures that are both energy-efficient and interpretable

OpenAI is releasing some sort of device related to its AI-powered coding tool, Codex, on July 15th. In a video posted to X on Monday, OpenAI shows a square-shaped device with several buttons, alongsid

arXiv:2606.21868v1 Announce Type: new Abstract: Modern Mixture-of-Experts (MoE) models place most of their parameters in expert layers, yet only a small fraction of those experts are used for any toke

arXiv:2605.09848v1 Announce Type: new Abstract: Electrocardiogram (ECG) interpretation is essential for diagnosing a wide range of cardiac abnormalities. While deep learning has shown strong potential

arXiv:2603.07053v2 Announce Type: replace Abstract: Scientists face significant visualization challenges as time-varying datasets grow in speed and volume, often requiring specialized infrastructure a

arXiv:2604.02811v2 Announce Type: replace-cross Abstract: Functional verification consumes over 50% of the IC development lifecycle, where SystemVerilog Assertions (SVAs) are indispensable for formal

arXiv:2406.06543v2 Announce Type: replace-cross Abstract: Deep learning has driven significant technological advancements, but its high energy consumption limits its use on battery-operated edge devic

Hugging Face Jobs integration with LeRobot enables users to run robotics tasks and training jobs on Hugging Face's infrastructure, streamlining the deployment and execution of robot learning models. T

As the automotive landscape accelerates toward software-defined vehicles, Cockpit Domain Controllers (CDCs) are becoming the core of next-generation in-cabin experiences. The ability to rapidly develo