Search: “hardware”

QuantFPFlow: Quantum Amplitude Estimation for Fokker--Planck Policy Optimisation in Continuous Reinforcement Learning

arXiv:2605.16429v1 Announce Type: cross Abstract: We introduce extbf{QuantFPFlow}, a reinforcement learning framework that integrates quantum amplitude estimation into the Fokker--Planck~(FP) formulat

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QuChaTeR: A Hybrid Quantum-Chaotic Temporal Framework for Earthquake Prediction

DGX agent

arXiv:2605.16454v1 Announce Type: new Abstract: Seismic prediction remains challenging due to the highly nonlinear and chaotic dynamics of earthquake signals. While classical deep learning models such

applicationsarxiv-cs-lg

19 May 2026

RGB-only Active 3D Scene Graph Generation for Indoor Mobile Robots

arXiv:2605.18197v1 Announce Type: cross Abstract: Current approaches to 3D scene graph generation rely on dedicated depth sensors, such as LiDAR or RGB-D cameras, for metric 3D reconstruction. This li

researcharxiv-cs-ai

SAMRI: Segment Any MRI

arXiv:2510.26635v3 Announce Type: replace-cross Abstract: Summary: SAMRI is an MRI-specialized adaptation of the Segment Anything Model achieving superior whole-body MRI segmentation, particularly for

local-aiarxiv-cs-cv

SEDD: Scalable and Efficient Dataset Deduplication with GPUs

model-releasesarxiv-cs-cl

arXiv:2501.01046v4 Announce Type: replace Abstract: Dataset deduplication is widely recognized as a crucial preprocessing step that enhances data quality and improves the performance of large language

Agents

Self-Supervised Bootstrapping of Action-Predictive Embodied Reasoning

arXiv:2602.08167v2 Announce Type: replace-cross Abstract: Embodied Chain-of-Thought (CoT) reasoning has significantly enhanced Vision-Language-Action (VLA) models, yet current methods rely on rigid te

agentsarxiv-cs-ai

SparseSAM: Structured Sparsification of Activations in Segment Anything Models

arXiv:2605.17633v1 Announce Type: cross Abstract: The Segment Anything Model (SAM) achieves strong open-vocabulary segmentation, but its ViT-based image encoders dominate inference latency and memory.

researcharxiv-cs-ai

Spiker-LL: An Energy-Efficient FPGA Accelerator Enabling Adaptive Local Learning in Spiking Neural Networks

arXiv:2605.18003v1 Announce Type: cross Abstract: Deploying adaptive intelligence at the edge remains challenging due to the high computational and energy cost of training neural models. Spiking Neura

local-aiarxiv-cs-ai

StatQAT: Statistical Quantizer Optimization for Deep Networks

arXiv:2605.17745v1 Announce Type: cross Abstract: Quantization is essential for reducing the computational cost and memory usage of deep neural networks, enabling efficient inference on low-precision

SVL: Spike-based Vision-language Pretraining for Efficient 3D Open-world Understanding

arXiv:2505.17674v2 Announce Type: replace Abstract: Spiking Neural Networks (SNNs) provide an energy-efficient way to extract 3D spatio-temporal features. However, existing SNNs still exhibit a signif

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Tactile-based Multimodal Fusion in Embodied Intelligence: A Survey of Vision, Language, and Contact-Driven Paradigms

model-releasesarxiv-cs-cv

arXiv:2605.17336v1 Announce Type: cross Abstract: Tactile sensing is a fundamental modality for embodied intelligence, offering unique and direct feedback on contact geometry, material properties, and

The last six months in LLMs in five minutes

model-releasessimon-willison

I put together these annotated slides from my five minute lightning talk at PyCon US 2026, using the latest iteration of my annotated presentation tool. # I presented this lightning talk at PyCon US 2

Toward Near-Real-Time Marine Oil Spill Detection in SAR Imagery using Quantum-Assisted SVM

arXiv:2605.17217v1 Announce Type: cross Abstract: Marine oil spills require rapid detection to mitigate severe ecological and economic damage. While satellite-based Synthetic Aperture Radar (SAR) prov

Two-Valued Symmetric Circulant Matrices: Applications in Deep Learning

arXiv:2605.16443v1 Announce Type: cross Abstract: Despite the success of deep neural networks in vision, medical diagnosis, and IoT scenarios, their deployment on resource-limited platforms poses seri

researcharxiv-cs-ai

Vidya: An AI-Driven Modular Pipeline for Archival Automation and Semantic Metadata Enrichment

arXiv:2605.16338v1 Announce Type: cross Abstract: The large-scale digitization of historical archives has created a paradox: 'dark data'-digital objects lacking metadata for retrieval. Manual archival

researcharxiv-cs-cl

You Had One Job: Per-Task Quantization Using LLMs' Hidden Representations

arXiv:2511.06516v3 Announce Type: replace Abstract: Many LLM applications require only narrow capabilities, yet standard post-training quantization (PTQ) methods allocate precision without considering

researcharxiv-cs-cl

A QUBO Formulation Framework for Kinematic Structure-Based Robot Design Optimization: A Robotic Hand Case Study

arXiv:2605.15510v1 Announce Type: new Abstract: This paper presents a quadratic unconstrained binary optimization-based formulation framework for robot design optimization using kinematic structure-le

applicationsarxiv-cs-ro

Adaptive Conformal Prediction for Quantum Machine Learning

arXiv:2511.18225v2 Announce Type: replace Abstract: Quantum machine learning seeks to leverage quantum computers to improve upon classical machine learning algorithms. Currently, robust uncertainty qu

Adaptive Outer-Loop Control of Quadrotors via Reinforcement Learning

arXiv:2605.16015v1 Announce Type: cross Abstract: Deep Reinforcement Learning (DRL) for quadrotor flight control typically relies on Domain Randomization (DR) for sim-to-real transfer, resulting in ov

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AgentStop: Terminating Local AI Agents Early to Save Energy in Consumer Devices

arXiv:2605.15206v1 Announce Type: cross Abstract: Autonomous agents powered by large language models (LLMs) are increasingly used to automate complex, multi-step tasks such as coding or web-based ques

local-aiarxiv-cs-ai

Automatic Construction of a Legal Citation Graph from 100 Million Ukrainian Court Decisions: Large-Scale Extraction, Topological Analysis, and Ontology-Driven Clustering

model-releasesarxiv-cs-cl

arXiv:2605.15362v1 Announce Type: new Abstract: Half a billion citation edges extracted from 100.7 million Ukrainian court decisions reveal that judicial citation structure encodes legal domain bounda

Designing Datacenter Power Delivery Hierarchies for the AI Era

arXiv:2605.16255v1 Announce Type: cross Abstract: Demand for AI accelerators is rapidly increasing rack power density, with projections approaching 1MW per deployment by 2027. This poses a major chall

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Diagonal Adaptive Non-local Observables on Quantum Neural Networks

model-releasesarxiv-cs-ai

arXiv:2605.15410v1 Announce Type: cross Abstract: Adaptive Non-local Observables (ANOs) have shown that making quantum observables dynamic can substantially enlarge the function space of Variational Q

Efficiently Solving Mixed-Hierarchy Games with Quasi-Policy Approximations

arXiv:2602.01568v2 Announce Type: replace-cross Abstract: Multi-robot coordination often exhibits hierarchical structure, with some robots' decisions depending on the planned behaviors of others. Whil

ElasticDiT: Efficient Diffusion Transformers via Elastic Architecture and Sparse Attention for High-Resolution Image Generation on Mobile Devices

arXiv:2605.15684v1 Announce Type: new Abstract: The Diffusion Transformer (DiT) architecture is the state-of-the-art paradigm for high-fidelity image generation, underpinning models like Stable Diffus

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Federated Learning of Spiking Neural Networks under Heterogeneous Temporal Resolutions

model-releasesarxiv-cs-lg

arXiv:2605.15355v1 Announce Type: new Abstract: Spiking neural networks (SNNs) are biologically inspired energy-efficient models that use sparse binary spike-based communication between neurons, makin

How Google Does It: Fleet-wide, large-scale A/B experimentation

When most people think of A/B experimentation, they think of button colors, landing page layouts, or checkout flows. At Google, many fundamental infrastructure improvements also need the rigor of A/B

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IO-SVD: Input-Output Whitened SVD for Adaptive-Rank LLM Compression

arXiv:2605.15626v1 Announce Type: new Abstract: Large language models deliver strong performance across language and reasoning tasks, but their storage and compute costs remain major barriers to deplo

Layer-wise Derivative Controlled Networks

arXiv:2605.15463v1 Announce Type: new Abstract: As machine learning models grow in complexity, they increasingly struggle with three conflicting demands: the need for high accuracy, the requirement fo

applicationsarxiv-cs-lg

Learning Structured Robot Policies from Vision-Language Models via Synthetic Neuro-Symbolic Supervision

model-releasesarxiv-cs-ro

arXiv:2604.02812v2 Announce Type: replace Abstract: Vision-Language Models (VLMs) have recently demonstrated strong capabilities in mapping multimodal observations to robot behaviors. However, most cu

llama.cpp adds MTP for the Qwen3.6 family This is a significant milestone for the local AI ecosystem. The performance jump with these change…

model-releasesclem-delangue--x

llama.cpp adds MTP for the Qwen3.6 family This is a significant milestone for the local AI ecosystem. The performance jump with these changes is massive and elevates local inference on commodity hardw

llama.cpp with MTP support makes local models fast enough to use as daily drivers 🚀 Qwen3.6-27B dense generation (on A10G): From 25 tok/s →…

model-releasesclem-delangue--x

llama.cpp with MTP support makes local models fast enough to use as daily drivers 🚀 Qwen3.6-27B dense generation (on A10G): From 25 tok/s → 45 tok/s (+78%). Two flags on llama-server: --spec-type draf

PerfCodeBench: Benchmarking LLMs for System-Level High-Performance Code Optimization

model-releasesarxiv-cs-cl

arXiv:2605.15222v1 Announce Type: cross Abstract: Large language models (LLMs) can often generate functionally correct code, but their ability to produce efficient implementations for performance-crit

Quantum Artificial Intelligence for Mission-Critical Systems: Foundations, Architectural Elements, and Future Directions

arXiv:2511.09884v2 Announce Type: replace Abstract: Mission critical (MC) applications such as defense operations, energy management, cybersecurity, and aerospace control require reliable, determinist

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Terrain Consistent Reference-Guided RL for Humanoid Navigation Autonomy

arXiv:2605.15517v1 Announce Type: new Abstract: We present a method for training reference-guided, perceptive reinforcement learning locomotion policies for humanoid robots in which reference trajecto

Whole-body motion planning and safety-critical control for aerial manipulation

arXiv:2511.02342v3 Announce Type: replace Abstract: Aerial manipulation combines the maneuverability of multirotors with the dexterity of robotic arms to perform complex tasks in cluttered spaces. Yet

LTX 2.3 is now supported in Comfyui-Mesh for splitting models across Ethernet or multigpu machines with Nvenc codec. Major vram fixes included for flux2/LTX model implementations in the node.

local-air-stablediffusion

Comfyui-Mesh now supports LTX 2.3 with the ability to distribute models across multiple GPUs or networked machines using Nvenc codec for video generation. The update includes significant VRAM optimiza

17 May 2026

Running Modern AI Image Models on a GTX 1060 6GB — A Practical Guide Tested & verified on NVIDIA GTX 1060 6GB (Pascal Architecture) · ComfyUI · May 2026 Written to counter the widespread misinformation that 'only SD 1.5 runs on 6GB VRAM'

local-air-stablediffusion

This guide demonstrates that modern AI image generation models beyond Stable Diffusion 1.5 can run on a GTX 1060 6GB GPU using optimization techniques and ComfyUI, countering the common misconception

17 May 2026

b9181

local-aillama-cpp-releases

llama.cpp release b9181 updated cpp-httplib to version 0.45.0 and included refactoring of the web UI to use new naming conventions with 'ui' instead of 'webui' throughout the codebase . The release pr

16 May 2026

A Prototyping Framework for Distributed Control of Multi-Robot Systems

arXiv:2605.15049v1 Announce Type: new Abstract: This paper presents a prototyping framework for distributed control of multi-robot systems, aimed at bridging theory and practical testing of distribute

local-aiarxiv-cs-ro

AI-Driven Optimization under Uncertainty for Mineral Processing Operations

arXiv:2512.01977v2 Announce Type: replace-cross Abstract: The global capacity for mineral processing must expand rapidly to meet the demand for critical minerals, which are essential for building the

applicationsarxiv-cs-ai

Analog RF Computing: A New Paradigm for Energy-Efficient Edge AI Over MU-MIMO Systems

arXiv:2605.14331v1 Announce Type: cross Abstract: Modern edge devices increasingly rely on neural networks for intelligent applications. However, conventional digital computing-based edge inference re

local-aiarxiv-cs-ai

b9165

local-aillama-cpp-releases

Release b9165 fixes a transform issue with the top entry in the release archive . The release includes pre-built binaries for multiple platforms including macOS, Linux, Android, and Windows with vario

Bellman Value Decomposition for Task Logic in Safe Optimal Control

arXiv:2602.19532v2 Announce Type: replace Abstract: Real-world tasks involve nuanced combinations of goal and safety specifications. In high dimensions, the challenge is exacerbated: formal automata b

Enhanced and Efficient Reasoning in Large Learning Models

arXiv:2605.14036v1 Announce Type: new Abstract: In current Large Language Models we can trust the production of smoothly flowing prose on the basis of the principles of machine learning. However, ther

applicationsarxiv-cs-ai

Evo-Depth: A Lightweight Depth-Enhanced Vision-Language-Action Model

arXiv:2605.14950v1 Announce Type: new Abstract: Vision-Language-Action models have emerged as a promising paradigm for robotic manipulation by unifying perception, language grounding, and action gener

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Gemini Live Agent Challenge: Announcing the winners and highlights

model-releasesgoogle-cloud-ai

The Gemini Live Agent Challenge is officially in the books! We challenged developers worldwide to break out of the traditional 'text box' paradigm by building next-generation AI agents. From our initi

Learning Dynamic Rope Manipulation Using Task-Level Iterative Learning Control

arXiv:2602.21302v2 Announce Type: replace Abstract: We introduce a Task-Level Iterative Learning Control method for dynamic manipulation of ropes. We demonstrate this method on a non-planar rope manip

researcharxiv-cs-ro