Search: “hardware”

arXiv:2606.22332v1 Announce Type: new Abstract: Tactile sensing is critical for contact-rich dexterous manipulation, yet it remains unclear which tactile abstractions a policy needs and when richer ta

arXiv:2606.23546v1 Announce Type: new Abstract: Transformer-based models underpin modern natural language processing but incur rapidly growing computational and energy costs. As training scales in bot

arXiv:2511.22699v4 Announce Type: replace Abstract: The landscape of high-performance image generation models is currently dominated by proprietary systems, such as Nano Banana Pro and Seedream 4.0. L

arXiv:2606.22145v1 Announce Type: new Abstract: Reinforcement learning (RL) is a powerful and convenient tool to modernize controller design. In this work, we study the zero-shot transfer of RL-based

Automated lint: 48 errors, 13 warnings, 3 info

arXiv:2606.12059v1 Announce Type: new Abstract: We address transformer attention on energy-constrained physical substrates. Softmax attention requires exponentiation and global reduction, operations w

arXiv:2503.22926v3 Announce Type: replace Abstract: Addressing the inherent low acquisition frequency limitation of 3D LiDAR to achieve high-frequency output has become a critical research focus in th

arXiv:2505.01458v2 Announce Type: replace-cross Abstract: Navigation and manipulation are core capabilities in Embodied AI, but training agents to perform them directly in the real world is costly, ti

arXiv:2606.09869v1 Announce Type: cross Abstract: Federated Learning (FL) combined with Split Learning (SL) is a privacy preserving paradigm that enables training deep neural networks (DNNs) on resour

arXiv:2606.10874v1 Announce Type: new Abstract: In quantum image processing, a fundamental step is encoding classical image data into quantum states. This can be achieved using methods such as Flexibl

arXiv:2606.09946v1 Announce Type: cross Abstract: Edge-AI systems increasingly require real-time CNN inference under strict energy, performance, security, and privacy constraints. Approximate computin

arXiv:2606.08584v1 Announce Type: new Abstract: Sparse coding provides a principled framework for signal representation by expressing an input as a linear combination of only a small number of basis f

arXiv:2602.21788v2 Announce Type: replace-cross Abstract: Scaling long-context capabilities is crucial for Large Language Models (LLMs). However, real-world data contain a large number of sequences wi

arXiv:2406.07318v3 Announce Type: replace Abstract: The utilisation of event cameras represents an important and swiftly evolving trend aimed at addressing the constraints of traditional video systems

arXiv:2505.20137v5 Announce Type: replace-cross Abstract: Predictive Coding (PC) offers a brain-inspired alternative to backpropagation for neural network training, described as a physical system mini

arXiv:2606.09117v1 Announce Type: cross Abstract: While Ising machines serve as advanced physical solvers for the Ising model,enabling applications in combinatorial optimization and neural network tra

arXiv:2606.09227v1 Announce Type: cross Abstract: The convergence of the 2026 European Union Safe and Sustainable by Design (SSbD) framework, Corporate Sustainability Due Diligence Directive (CSDDD),

The search results did not provide specific information about the b9564 release. Based on the context of llama.cpp releases and the pattern observed with nearby releases (b9542, b9543, b9544, etc.), I

arXiv:2509.11740v2 Announce Type: replace Abstract: Autonomous stocking in retail environments, particularly supermarkets, presents challenges due to dynamic human interactions, constrained spaces, an

Given how badly burned anyone who took Apple's 2024 WWDC Apple Intelligence announcements at face value was, I'm holding to a strict 'I'll believe it when I see it' policy for everything they announce

The search did not return specific details about the b9547 release. Based on the repository context and release naming convention, b9547 is a build number for llama.cpp, an open-source C/C++ implement

Release b9549 of llama.cpp adds support for the Gemma4 MTP model architecture . The release includes pre-built binaries for multiple platforms including macOS, Linux, Android, and Windows with various

llama.cpp is a project for LLM inference in C/C++ . Release b9551 is a build version from the llama.cpp project's GitHub releases, following the project's rapid development cycle where multiple releas

Automated lint: 47 errors, 12 warnings, 3 info

arXiv:2606.06034v1 Announce Type: cross Abstract: Matrix inversion in chunk-wise parallel linear attention is a major bottleneck for long-context modeling, particularly on NPUs, where forward-substitu

arXiv:2606.06011v1 Announce Type: new Abstract: In this work, we propose a framework that combines multi-agent reinforcement learning (MARL) with model-based control to achieve safe, dynamically feasi

arXiv:2606.04746v1 Announce Type: new Abstract: Multi-Agent Path Finding (MAPF) algorithms are increasingly used to plan motion for robot teams in industrial warehouses and robotic shared workspaces,

its been such fun befriending Pari and seeing him completely reinvent his company for the agentic era, WHILE having the most insanely stacked customer base I've ever seen in the hardest engineering do

arXiv:2606.04582v1 Announce Type: cross Abstract: Real-time monitoring of the temperature distribution within components and sub-structures is a challenging topic in many systems due to restrictions o

At Google Cloud, our goal is to let you run large-scale analytical and data science workloads with maximum efficiency so you can process big data pipelines, machine learning, and ETL tasks. We recentl

arXiv:2606.03675v1 Announce Type: new Abstract: Methane is a potent greenhouse gas, and detecting leaks early via hyperspectral satellite imagery can help climate change mitigation efforts. Meanwhile,

The search results show general llama.cpp information and references to other recent builds (like b9484), but the specific details for b9487 were not clearly accessible. Based on the context from llam

arXiv:2606.03557v1 Announce Type: new Abstract: As generative AI capabilities expand, AI-driven virtual worlds face a growing architectural challenge. Users interact through in-world interfaces in mul

arXiv:2602.20217v2 Announce Type: replace-cross Abstract: Self-speculative decoding (SSD) accelerates LLM inference by skipping layers to create an efficient draft model, yet existing methods often re

arXiv:2606.00130v1 Announce Type: cross Abstract: We study Automatically Differentiable Nonlinear Tensor Networks (ADNTNs), a family of structured weight generators whose compact core tensors are trai

What happens when your workload fails in one region but you need access to service? This is a common case for availability and uptime. With recent enhancement to the Kubernetes ecosystem and capabilit

arXiv:2606.01577v1 Announce Type: new Abstract: Methane is a major driver of near-term climate change, and rapidly identifying its emission sources is a critical climate intervention. Spaceborne hyper

arXiv:2606.01862v1 Announce Type: cross Abstract: Translating user intents into physical radio signals represents the critical yet notoriously tedious final step in wireless prototyping, as it require

arXiv:2606.01038v1 Announce Type: new Abstract: This paper presents a new robust integrated planning and control (IPC) strategy for multirotor uncrewed aerial vehicles. We propose a nonlinear model pr

arXiv:2511.21513v2 Announce Type: replace Abstract: Deploying Transformer models on edge devices is limited by latency and energy budgets. While INT8 quantization effectively accelerates the primary m

arXiv:2605.30952v1 Announce Type: new Abstract: Two recent results have reshaped quantum Gaussian processes (QGPs). On the one hand, itet{lowe2025assessing} rule out the exponential speedups claimed b

arXiv:2605.30383v1 Announce Type: cross Abstract: Scaling individual robot capabilities is common but costly. Here we investigate a system-level design question in real-world multi-robot coordination:

arXiv:2605.29359v1 Announce Type: cross Abstract: Compute governance proposals often rely on the assumption that frontier AI training requires large, detectable computing clusters. However, recent adv

arXiv:2510.15340v2 Announce Type: replace-cross Abstract: State preparation is a cornerstone of quantum technologies, underpinning applications in computation, communication, and sensing. Its importan

arXiv:2605.27445v1 Announce Type: cross Abstract: Deploying Large Language Model (LLM) applications, particularly those relying on Retrieval-Augmented Generation (RAG), remains challenging due to high

arXiv:2506.05012v2 Announce Type: replace Abstract: Matching the swimming efficiency and agility of fish has remained an elusive goal in underwater robotics. Such locomotion capabilities rely on compl