Search: “hardware”

Amortized Nonlinear Model Predictive Control

arXiv:2606.05840v1 Announce Type: cross Abstract: Nonlinear Model Predictive Control requires solving a constrained nonlinear program (NLP) in real-time at every sampling instant, a computational bott

Can We Predict The Human Preference For Text-to-Image Content Prior To Generation And Is It Even Useful To Do So?

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

DGX agent

arXiv:2606.05478v1 Announce Type: new Abstract: Diffusion Models (DM) have revolutionized text-driven generation by enabling the synthesis of high-quality, photorealistic visual content from user prom

researcharxiv-cs-cv

5 Jun 2026

Deep Learning-based 3D Oral Cavity Reconstruction Using 2D Intraoral Images

arXiv:2606.05998v1 Announce Type: new Abstract: Oral 3D modelling is one of the most essential stages in dentistry, and many different approaches, such as impression taking and intraoral scanning, are

researcharxiv-cs-cv

EgoHumanoid: Unlocking In-the-Wild Loco-Manipulation with Robot-Free Egocentric Demonstration

arXiv:2602.10106v2 Announce Type: replace Abstract: Human demonstrations offer rich environmental diversity and scale naturally, making them an appealing alternative to robot teleoperation. While this

HANDOFF: Humanoid Agentic Task-Space Whole-Body Control via Distilled Complementary Teachers

arXiv:2606.06493v1 Announce Type: new Abstract: For a humanoid robot to be deployed in the real world, the choice of command space (i.e., the interface between task planning and whole-body control) is

LadderMan: Learning Humanoid Perceptive Ladder Climbing

arXiv:2606.05873v1 Announce Type: cross Abstract: Humanoid robots hold great promise for operating in human-centered environments, yet ladder climbing remains one of the most challenging tasks due to

safetyarxiv-cs-cv

MoDex: A Diffusion Policy for Sequential Multi-Object Dexterous Grasping

arXiv:2606.05407v1 Announce Type: new Abstract: This work addresses sequentially grasping multiple objects with a single dexterous hand without releasing those already held. Most dexterous grasping me

TAGA: Terrain-aware Active Gaze Learning for Generalizable Agile Humanoid Locomotion

arXiv:2606.05880v1 Announce Type: new Abstract: Agile humanoid locomotion across diverse challenging terrain demands both wide perceptual coverage and precise local geometry understanding. Motivated b

local-aiarxiv-cs-ro

AutoNumerics-Zero: Automated Discovery of State-of-the-Art Mathematical Functions

arXiv:2312.08472v2 Announce Type: replace-cross Abstract: Transcendental functions, such as the exponential, are central to scientific computing, yet they cannot be natively calculated by digital hard

CodegenBench: Can LLMs Write Efficient Code Across Architectures?

arXiv:2606.04023v1 Announce Type: cross Abstract: While large language models (LLMs) have been extensively evaluated on code generation tasks for general-purpose programming and GPU-accelerated enviro

DiffAero: A GPU-Accelerated Differentiable Simulation Framework for Efficient Quadrotor Policy Learning

arXiv:2509.10247v1 Announce Type: cross Abstract: This letter introduces DiffAero, a lightweight, GPU-accelerated, and fully differentiable simulation framework designed for efficient quadrotor contro

safetyarxiv-cs-ai

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats

arXiv:2606.04115v1 Announce Type: cross Abstract: Quantizing large language models (LLMs) to low-precision floating-point representations is central to efficient deployment, yet applying a single bit-

HighTide: An Agent-Curated Open-Source VLSI Benchmark Suite

arXiv:2606.04126v1 Announce Type: cross Abstract: We introduce HighTide, an evolving AI-assisted benchmark suite. Specifically, the contributions are: (i) a diverse open-source suite spanning multiple

L^3: Large Lookup Layers

arXiv:2601.21461v3 Announce Type: replace-cross Abstract: Modern sparse language models typically achieve sparsity through Mixture-of-Experts (MoE) layers, which dynamically route tokens to dense MLP

researcharxiv-cs-ai

LiftQuant: Continuous Bit-Width LLM via Dimensional Lifting and Projection

arXiv:2606.04050v1 Announce Type: cross Abstract: Existing quantization methods are fundamentally limited by rigid, integer-based bit-widths (e.g., 2, 3-bit), resulting in a ``deployment gap' where La

NLLog: Lightweight, Explainable SOC Anomaly Detection via Log-to-Language Rewriting

arXiv:2606.04957v1 Announce Type: cross Abstract: System-generated logs underpin security monitoring, yet their rigid template-based format hinders both automated analysis and human comprehension. We

PerceptTwin: Semantic Scene Reconstruction for Iterative LLM Planning and Verification

arXiv:2606.04226v1 Announce Type: cross Abstract: Simulation environments are useful for both robot policy learning and planning verification and validation. Traditionally, the process of creating a s

safetyarxiv-cs-ai

Recover-LoRA for Aggressive Quantization: Reclaiming Accuracy in 2-Bit Language Models via Low-Rank Adaptation with Knowledge Distillation on Synthetic Data

arXiv:2606.04238v1 Announce Type: cross Abstract: Aggressive weight quantization to 2-bit precision offers substantial throughput and memory gains for large language model (LLM) inference, but typical

local-aiarxiv-cs-ai

Applications

SSSD: Simply-Scalable Speculative Decoding

arXiv:2411.05894v3 Announce Type: replace-cross Abstract: Speculative Decoding has emerged as a popular technique for accelerating inference in Large Language Models. However, most existing approaches

applicationsarxiv-cs-ai

Teaching Robots to Say 'I Don't Know' : SENTINEL for Uncertainty-Aware SLAM

arXiv:2606.04853v1 Announce Type: new Abstract: Low-cost 2D LiDARs lack the intensity channel that higher-end sensors use to diagnose measurement failures, yet they are widely used on educational and

Applications

The Differentiable Auditory Loop (DAL): An ML Framework for Hyper-Personalized Hearing Aids

arXiv:2606.04103v1 Announce Type: cross Abstract: Conventional hearing aids rely on fixed, frequency-dependent amplification and compression to manage reduced sensitivity, which often fails to provide

applicationsarxiv-cs-ai

TransTac: Visuo-Tactile Modality Transition via Ultraviolet-Encoded Transparent Elastomers

arXiv:2606.04477v1 Announce Type: new Abstract: Vision-based tactile sensors (VBTS) recover high-resolution contact geometry but typically rely on opaque elastomer layers that prevent visual transpare

Applications

Uncertainty-Aware End-to-End Co-Design of Neural Network Processors: From Training and Mapping to Fabrication

arXiv:2606.04850v1 Announce Type: cross Abstract: Designing a neural network processor is an end-to-end co-design problem: network architecture and training budget determine the inference workload; ha

applicationsarxiv-cs-ai

Agents

Vectorized Online POMDP Planning

arXiv:2510.27191v5 Announce Type: replace-cross Abstract: Planning under partial observability is an essential capability of autonomous robots. The Partially Observable Markov Decision Process (POMDP)

agentsarxiv-cs-ai

A Measurement-Driven Digital Twin Architecture for Plant-Level Biomass Estimation and Growth Forecasting in Hydroponic Systems

arXiv:2606.02796v1 Announce Type: new Abstract: Alternatives to soil-based horticulture, such as hydroponics, have been developed to respond to food distribution concerns for dense urban centers. A ne

Agent libOS: A Library-OS-Inspired Runtime for Long-Running, Capability-Controlled LLM Agents

arXiv:2606.03895v1 Announce Type: cross Abstract: Large language model (LLM) agents are evolving from request-response assistants into long-running software actors: they maintain state across model ca

local-aiarxiv-cs-ai

ArrowFlow: Hierarchical Machine Learning in the Space of Permutations

model-releasesarxiv-cs-lg

arXiv:2604.04087v2 Announce Type: replace Abstract: We introduce ArrowFlow, a machine learning architecture that operates entirely in the space of permutations. Its computational units are ranking fil

Assessing Region-Level EEG Contributions to Cognitive Workload Prediction

arXiv:2606.02598v1 Announce Type: new Abstract: Accurate and generalizable estimation of cognitive workload from electroencephalography (EEG) is critical for human-centered and safety-critical systems

safetyarxiv-cs-lg

ATLAS: A Large-Scale Evaluation Benchmark for Adversarial LiDAR Perception

model-releasesarxiv-cs-cv

arXiv:2606.02924v1 Announce Type: new Abstract: Autonomous driving perception is typically evaluated on clean benchmark data, yet real-world deployment requires robustness to rare, structured, and pot

AURA: Action-Gated Memory for Robot Policies at Constant VRAM

arXiv:2606.02775v1 Announce Type: new Abstract: The KV-cache is the right memory for datacenters but the wrong memory for robots. Datacenter inference batches many short requests and resets them, amor

Bionic Human-Motion Style Transfer for Physically Executable Whole-Body Control of Humanoid Robots

arXiv:2606.03536v1 Announce Type: new Abstract: Expressive whole-body motion is important for humanoid robots operating in human environments, where robots are expected to move stably while presenting

CourseTimeQA: A Lecture-Video Benchmark and a Latency-Constrained Cross-Modal Fusion Method for Timestamped QA

model-releasesarxiv-cs-cl

arXiv:2512.00360v2 Announce Type: replace Abstract: We study timestamped question answering over educational lecture videos under a single-GPU latency/memory budget. Given a natural-language query, th

Dynamic Short Convolutions Improve Transformers

arXiv:2606.03825v1 Announce Type: cross Abstract: Transformers have become the dominant architecture for large language models, largely due to the scalability and flexibility of attention, feed-forwar

safetyarxiv-cs-cl

Evaluating LLMs' Effectiveness on Real-World Consumer Device Repair Questions

arXiv:2606.03331v1 Announce Type: cross Abstract: Consumer device repair is an important but underexplored testbed for large language models (LLMs). Repair tasks require reasoning over incomplete prob

Fixed-Time Dynamic Landing of Quadrotors using Adaptive Unscented Kalman Filtering and Nonlinear Model Predictive Control

arXiv:2606.02658v1 Announce Type: new Abstract: This paper introduces an estimation and control framework for dynamic landing of multi-rotor uncrewed aerial vehicles on moving platforms. The proposed

FlashMLA-ETAP: Efficient Transpose Attention Pipeline for Accelerating MLA Inference on NVIDIA H20 GPUs

arXiv:2506.01969v3 Announce Type: replace-cross Abstract: Efficient inference of Multi-Head Latent Attention (MLA) is challenged by deploying the DeepSeek-R1 671B model on a single Multi-GPU server. T

KForge: LLM-Driven Cross-Platform Kernel Generation for AI Accelerators

model-releasesarxiv-cs-lg

arXiv:2606.02963v1 Announce Type: new Abstract: Production inference increasingly targets a heterogeneous mix of accelerators. Agentic pipelines interleave reasoning, tool calls, and multi-agent coord

Latent Activation Editing: Inference-Time Refinement of Learned Policies for Safer Multirobot Navigation

arXiv:2509.20623v2 Announce Type: replace Abstract: Reinforcement learning has enabled significant progress in complex domains such as coordinating and navigating multiple quadrotors. However, even we

Link Prediction or Perdition: the Seeds of Instability in Knowledge Graph Embeddings

arXiv:2606.03365v1 Announce Type: new Abstract: Embedding models (KGEMs) constitute the main link prediction approach to complete knowledge graphs. Standard evaluation protocols emphasize rank-based m

LiveBand: Live Accompaniment Generation in the Audio Domain

arXiv:2606.03803v1 Announce Type: cross Abstract: We present LiveBand, a real-time system that generates high-fidelity music accompaniments to live audio input, respecting strict causal constraints. O

Multi-Segment Attention: Enabling Efficient KV-Cache Management for Faster Large Language Model Serving

arXiv:2606.02964v1 Announce Type: cross Abstract: Large Language Model (LLM) inference relies on key-value (KV) caches to avoid redundant attention computation. While approximate KV cache retention te

safetyarxiv-cs-cl

NetKV: Network-Aware Decode Instance Selection for Disaggregated LLM Inference

arXiv:2606.03910v1 Announce Type: cross Abstract: Disaggregated LLM inference forces the KV cache to traverse the datacenter network before decoding begins, so transfer time enters directly into the T

local-aiarxiv-cs-ai

OASIS: Outlier-Aware LUT-Based GEMM with Dual-Side Quantization for LLM Inference Acceleration

arXiv:2507.23035v4 Announce Type: replace Abstract: Large language models (LLMs) have demonstrated impressive capabilities across a wide range of applications, but demand substantial memory and comput

Optimizing Explicit Unit-Distance Lower-Bound Certificates

arXiv:2606.03419v1 Announce Type: cross Abstract: The 2026 disproof of Erdos's unit-distance conjecture and Sawin's subsequent explicit quantitative refinement show that the maximum number u(n) of uni

PrimeSVT: An Automated Memory-aware Pruning Framework with Prioritized Compression Policy for Spiking Vision Transformers

arXiv:2606.03428v1 Announce Type: cross Abstract: The large sizes of Spiking Vision Transformers (SViTs) still hinder their embedded implementation, highlighting the need for model compression. State-

safetyarxiv-cs-ai

PSViT: A Methodology for Structurally Pruning Spiking Vision Transformers

arXiv:2606.03257v1 Announce Type: cross Abstract: Spiking Vision Transformer (SViT) models are promising low-power ViT models for solving vision-based tasks with state-of-the-art performance. However,

researcharxiv-cs-ai

QUIVER: Quantum-Informed Views for Enhanced Representations in Large ML Models

model-releasesarxiv-cs-lg

arXiv:2606.02785v1 Announce Type: new Abstract: Large machine learning models benefit substantially from multimodal inputs that provide a complementary view of the same example. We introduce QUIVER (Q

Agents

Reproducibility is the New Copyleft: Defining AGI-oriented Reproducible Builds

arXiv:2606.03019v1 Announce Type: cross Abstract: Copyleft, as implemented in licenses such as the GNU General Public License, was a legal hack that used copyright to guarantee user freedom by tying t

agentsarxiv-cs-ai