Search: “hardware”

A prior-free blind detection of information leakage from model predictions

arXiv:2606.11267v1 Announce Type: new Abstract: Data leakage -- contamination of a model with information unavailable at baseline -- is the dominant reproducibility failure in machine-learning-based s

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Model Releases

APEX: A Network-Native Time-Series Foundation Model for Forecasting and Anomaly Detection for Wireless Edge Operations

DGX agent

arXiv:2606.11553v1 Announce Type: new Abstract: Generic time-series foundation models transfer poorly to wireless network telemetry whose signals are bursty, zero-inflated, and coupled across protocol

model-releasesarxiv-cs-lg

11 Jun 2026

Blind Dexterous Grasping via Real2Sim2Real Tactile Policy Learning

arXiv:2606.11767v1 Announce Type: cross Abstract: Blind grasping with a dexterous hand is a crucial manipulation capability. Nevertheless, learning such tactile-only policies for real robots remains c

Compiler-First State Space Duality and Portable O(1) Autoregressive Caching for Inference

arXiv:2603.09555v2 Announce Type: replace-cross Abstract: High-throughput Mamba-2 inference is usually tied to fused CUDA and Triton kernels, limiting portability across accelerator backends. We show

DroneShield-AI: A Multi-Modal Sensor Fusion Framework for Real-Time Autonomous Drone Threat Detection, Behavioral Intent Classification, and Swarm Intelligence in Contested Airspace

model-releasesarxiv-cs-cv

arXiv:2606.11687v1 Announce Type: new Abstract: Unmanned Aerial Vehicle (UAV) threats have emerged as a defining security challenge of the 21st century. This paper presents DroneShield-AI, a unified o

DuoBench: A Reproducible Benchmark for Bimanual Manipulation in Simulation and the Real World

model-releasesarxiv-cs-ai

arXiv:2606.11901v1 Announce Type: cross Abstract: Bimanual robot systems substantially expand manipulation capabilities, but coordinating two arms introduces additional control complexity and failure

Energy Use of AI Inference, Efficiency Pathways, and Test-Time Scaling

arXiv:2509.20241v2 Announce Type: replace Abstract: As AI inference scales to billions of queries, estimates of per-query energy use are increasingly important for capacity planning, efficiency interv

safetyarxiv-cs-lg

FACTR 2: Learning External Force Sensing for Commodity Robot Arms Improves Policy Learning

arXiv:2606.12406v1 Announce Type: cross Abstract: Contact-rich manipulation requires force sensitivity, but many robot arms lack dedicated force sensors due to their high cost. We present Neural Exter

Fast-SDE: Efficient Single-Microphone Sound Source Distance Estimation in Reverberant Environments

arXiv:2606.12339v1 Announce Type: cross Abstract: Sound source distance estimation (SDE) is a critical capability in human-robot interaction. An inappropriate interaction distance not only reduces the

applicationsarxiv-cs-ro

Higher-Order Token Interactions via Quantum Attention

arXiv:2606.11673v1 Announce Type: cross Abstract: Standard dot-product self-attention computes, in a single layer, only pairwise (order-2) interactions between tokens; representing a generic order-k i

HiPi: Reproducible High-Fidelity Piezoresistive Sensors for Robotic Manipulation

arXiv:2606.11372v1 Announce Type: new Abstract: Piezoresistive tactile sensors are attractive for robotic manipulation because they are thin, lightweight, low-cost, and scalable to dense large-area se

applicationsarxiv-cs-ro

I built a 100% local, CPU-only voice loop for Ollama — talk to your models hands-free (Silero VAD + Parakeet STT + Supertonic TTS 3)

A developer created a fully local, CPU-based voice interface for Ollama that enables hands-free conversation with AI models by combining three open-source components: Silero VAD (voice activity detect

local-air-ollama

Learning What to Say to Your VLA: Mostly Harmless Vision Language Action Model Steering

arXiv:2606.12299v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models provide a natural language interface to robot control, but the mapping from language to behavior is often brittle

safetyarxiv-cs-lg

Neural-Parameterized Cellular Automata for Wildfire Spread

arXiv:2606.11676v1 Announce Type: cross Abstract: Traditional wildfire models rely on rigid, low-dimensional parameters and static fuel maps, frequently underpredicting fire spread. To address this we

Physics-Distilled Neural Network enabled by Large Language Models for Manufacturing Process-Property Predictive Modeling

arXiv:2606.11605v1 Announce Type: cross Abstract: Predicting process-property relationships in manufacturing is often challenged by high experimental costs and the limited interpretability of complex

applicationsarxiv-cs-ai

PLUME: Probabilistic Latent Unified World Modeling and Parameter Estimation for Multi-Finger Manipulation

model-releasesarxiv-cs-ro

arXiv:2606.11396v1 Announce Type: new Abstract: Dexterous manipulation with multi-finger hands can be sensitive to physical parameters such as object shape, pose, and friction coefficients. While simu

Privacy-Preserving Federated Autoencoder for ECG Anomaly Detection on Edge Devices

arXiv:2606.11556v1 Announce Type: cross Abstract: Continuous electrocardiography (ECG) monitoring could surface rhythm abnormalities before they escalate into cardiovascular events. However, a deploya

applicationsarxiv-cs-ai

Running Gemma 4 QAT 12B on an 8GB GPU at 16k context — measured the KV-cache tradeoffs

This post discusses running Google's Gemma 4 QAT (Quantized Aware Training) 12B model on a GPU with 8GB of memory while maintaining a 16k token context window. The author likely shares performance ben

model-releasesr-ollama

Scaling Laws of Global Weather Models

arXiv:2602.22962v2 Announce Type: replace Abstract: Data-driven models are revolutionizing weather forecasting. To optimize training efficiency and model performance, this paper analyzes empirical sca

TacCoRL: Integrating Tactile Feedback into VLA via Simulation

arXiv:2606.11743v1 Announce Type: cross Abstract: Vision-language-action (VLA) models provide strong visual, language, and action priors for robot manipulation, but visual observations alone often mis

safetyarxiv-cs-lg

The Environmental Cost of LLMs in AIED: Reporting and Practices

arXiv:2606.11215v1 Announce Type: cross Abstract: Large Language Model (LLM) usage in recent years has become increasingly widespread in the Artificial Intelligence in Education (AIED) community. Whil

applicationsarxiv-cs-ai

Time-multiplexed layer reuse for physical neural networks

arXiv:2511.00044v3 Announce Type: replace Abstract: Physical neural networks (PNNs) are promising candidates for next-generation computing, but existing demonstrations remain several orders of magnitu

AdaGC: Enhancing LLM Pretraining Stability via Adaptive Gradient Clipping

arXiv:2502.11034v3 Announce Type: replace Abstract: Loss spikes remain a persistent obstacle in large-scale language model pretraining. While previous research has attempted to identify the root cause

AgniNav: Configuration-Driven Cross-Embodiment Local Planning for Robot Navigation

model-releasesarxiv-cs-ro

arXiv:2606.10903v1 Announce Type: new Abstract: Monocular local navigation is attractive for lightweight robots, but existing vision-based policies often couple perception to a specific body, camera h

b9592

The search results did not contain specific information about the b9592 release. Based on the available information, b9592 is a version release from the llama.cpp project, which is an LLM inference sy

Agents

Beyond Static Evaluation: Co-Evolutionary Mechanisms for LLM-Driven Strategy Evolution in Adversarial Games

arXiv:2606.10389v1 Announce Type: new Abstract: Recent advances in LLM-driven code evolution have enabled automated discovery by iteratively generating and improving programs. However, applying these

agentsarxiv-cs-ai

Continual LLM Upcycling: A Predictor-Gated Bank-Wise Sparsity Training Recipe for Dense-to-Sparse LLMs

model-releasesarxiv-cs-cl

arXiv:2606.10722v1 Announce Type: new Abstract: We study dense-to-sparse continual training as a way to construct channel-sparse large language models from dense checkpoints. Starting from a Qwen2.5-8

FG-Attn: Leveraging Fine-Grained Sparse Attention in Video Diffusion Models

arXiv:2509.16518v2 Announce Type: replace Abstract: Using diffusion transformers for media generation may require evaluating attention over extremely long sequences, with attention layers accounting f

researcharxiv-cs-cv

Hierarchical Policies from Verbal and Egocentric Human Signals for Natural Human-Robot Interaction

arXiv:2606.10276v1 Announce Type: cross Abstract: For natural human-robot interaction, a robot must understand human intent expressed not only through language but also through nonverbal signals such

HydraCIL: Decoupled Class-Incremental Learning through Prototype-Guided Multi-Head Classifiers

arXiv:2606.09960v1 Announce Type: cross Abstract: We present HydraCIL, a decoupled continual learning model based on prototype-guided multi-head classifiers, targeting sustainable deployment in embedd

IMPACT: Learning Internal-Model Predictive Control for Forceful Robotic Manipulation

arXiv:2606.10818v1 Announce Type: cross Abstract: Real-world robotic manipulation tasks often involve forceful interactions with the environment, such as using tools of varying weights, transporting o

safetyarxiv-cs-cv

PRISM: Parallel Residual Iterative Sequence Model

arXiv:2602.10796v3 Announce Type: replace Abstract: Generative sequence modeling faces a fundamental tension between the expressivity of Transformers and the efficiency of linear sequence models. Exis

Robotic Nonprehensile Object Transportation with a Hanging Tray

arXiv:2606.10039v1 Announce Type: new Abstract: We consider the nonprehensile object transportation task known as the waiter's problem, in which a robot must move an object balanced on a tray from one

researcharxiv-cs-ro

ros2probe: Non-intrusive, Kernel-selective Observability for Robot Operating System 2 Middleware

arXiv:2606.10746v1 Announce Type: new Abstract: Robot Operating System 2 (ROS 2), the de facto standard middleware framework for robots, runs each robot as a graph of nodes communicating over the Data

researcharxiv-cs-ro

Uncovering Vulnerability of Vision-Language-Action Models under Joint-Level Physical Faults

arXiv:2606.10501v1 Announce Type: new Abstract: Deploying Vision-Language-Action (VLA) models in real robotic systems requires robustness not only to semantic and perceptual variations, but also to em

safetyarxiv-cs-ro

What is the best open sourced image model?

local-air-stablediffusion

The best open-source image generation models in 2026 include FLUX.1 [schnell], Stable Diffusion 3.5 Large, HiDream-I1-Full, SANA-Sprint 1.6B, and HunyuanImage-3.0 . FLUX.1 [dev] holds the crown for ph

YUBI: Yielding Universal Bidigital Interface for Bimanual Dexterous Manipulation at Scale

arXiv:2606.10244v1 Announce Type: cross Abstract: We introduce Yielding Universal Bidigital Interface (YUBI), a finger-aligned gripper designed to enable intuitive, ergonomic, and scalable data collec

Tutorials

AetheRock: An Arm-Worn Robot Teaching System for Force-Guided Vision-Tactile Learning

arXiv:2606.09777v1 Announce Type: new Abstract: Force and tactile sensing are indispensable in contact-rich manipulation. However, force-aware robot learning faces critical challenges due to the incom

tutorialsarxiv-cs-ro

AgentCompile: An LLM-Guided Compiler for Direct CUDA Inference

model-releasesarxiv-cs-ai

arXiv:2606.07665v1 Announce Type: cross Abstract: Transformer inference increasingly depends on specialized compiler and runtime support, but real model graphs still require semantic decisions about w

Aperon Technical Report: Hierarchical No-Pointer Tangent-Local Search for High-Dimensional Approximate Nearest Neighbors

arXiv:2606.08813v1 Announce Type: cross Abstract: We present HNTL (Hierarchical No-pointer Tangent-Local), the core vector indexing and candidate generation framework of the Aperon vector memory syste

APEX4: Efficient Pure W4A4 LLM Inference via Intra-SM Compute Rebalancing

model-releasesarxiv-cs-ai

arXiv:2606.08761v1 Announce Type: cross Abstract: W4A4 quantization promises full utilization of INT4 Tensor Cores, yet group dequantization overhead on CUDA Cores has driven existing systems to mixed

b9572

Release b9572 of llama.cpp fixes a bug in the ggml-cpu rms_norm_back function that produced incorrect output under in-place aliasing conditions. The release includes multiple pre-built binaries for va

b9573

b9573 is a build release of llama.cpp, an open-source C/C++ project for LLM inference that aims to enable language model inference with minimal setup and state-of-the-art performance on various hardwa

b9578

Release b9578 of llama.cpp includes a refactor of video subprocess handling in the mtmd (multi-threaded multi-device) component via pull request #24316 . The release provides prebuilt binaries across

b9581

llama.cpp b9581 is a release that includes optimization for Vulkan backend memory usage, specifically reducing iq1 shared memory usage for mul_mm operations. Released on June 9, 2026 , this build prov

Beyond FLOPs: Benchmarking Real Inference Acceleration of LLM Pruning under a GEMM-Centric Taxonomy

arXiv:2606.09080v1 Announce Type: new Abstract: Pruning has emerged as a dominant paradigm for accelerating large language model (LLM) inference, spanning a broad spectrum of methods that remove compu

CANS: Accelerating Multiuser Collaborative Edge Inference via Cooperative Autodidactic NeuroSurgeon

arXiv:2606.09175v1 Announce Type: cross Abstract: Recently, mobile edge computing (MEC)-enabled collaborative deep neural network (DNN) inference has emerged as a promising approach for delivering int

CT-VAM: A Cerebello-Thalamic-Inspired Vision-Action Model for Efficient Visuomotor Control

arXiv:2606.09572v1 Announce Type: cross Abstract: Vision-language-action models have shown strong promise for robot manipulation, yet raw language is primarily needed to specify task intent rather tha