Search: “hardware”

Lightweight and Resource-Efficient Perception for Robotic Guide Dogs

arXiv:2610.03187v1 Announce Type: cross Abstract: Multi-camera streaming perception is increasingly deployed on heterogeneous edge platforms shared with co-resident workloads, yet accelerator placemen

5 Oct 2026

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Probe the Harness: Setup Checks for Stale-Data RL Comparisons in Language Models

DGX agent

arXiv:2610.02911v1 Announce Type: cross Abstract: Methods for training language models on stale samples are judged by comparisons against importance-corrected baselines. We show that details of the ex

hardwarearxiv-cs-cl

5 Oct 2026

Tailoring the Quantization Space for 1-Bit KV Cache Compression

arXiv:2610.03027v1 Announce Type: cross Abstract: The key-value (KV) cache becomes a major memory bottleneck in long-context LLM inference, placing substantial pressure on memory capacity and bandwidt

5 Oct 2026

Windfoil: Closed-Form Coverage for Real-Time and Differentiable Vector Graphics

arXiv:2610.02468v1 Announce Type: cross Abstract: We present Windfoil, a GPU-friendly algorithm that treats rasterisation and differentiable vector graphics as two sides of the same problem by evaluat

5 Oct 2026

CAST: Cost-Aware Speculative Trees from One-Pass Block Drafters

arXiv:2610.00321v1 Announce Type: cross Abstract: Speculative decoding accelerates large language model inference by drafting future tokens cheaply and verifying them with the target model in parallel

DRelay: Global Draft Context for Prefix-Aware Parallel Speculative Decoding Repair

arXiv:2610.01439v1 Announce Type: new Abstract: Parallel drafting reduces the drafting overhead of speculative decoding for large language models (LLMs), but its gains remain limited by the accepted p

FastCI: Efficient GPU-Intensive CI for LLM Training Frameworks

arXiv:2610.01967v1 Announce Type: new Abstract: As large language models (LLMs) keep growing in size and complexity, their training frameworks evolve at a rapid pace as well. Therefore, continuous int

ibUMAP: Coherent and Scalable Field Evaluation for UMAP Optimization

arXiv:2610.01445v1 Announce Type: new Abstract: UMAP achieves scalable layout optimization through stochastic negative sampling. However, this stochasticity can lead to unstable embeddings across reru

LESS: Lightweight Evolutionary Supernet Search in Minutes

arXiv:2610.01468v1 Announce Type: cross Abstract: Low-cost NAS must both explore high-performing architectures and identify them reliably, yet reducing evaluation cost often weakens the fidelity of ca

TensorCommitments: A Lightweight Verifiable Inference for Language Models

arXiv:2602.12630v2 Announce Type: replace-cross Abstract: Most large language models (LLMs) run on external clouds: users send a prompt, pay for inference, and must trust that the remote GPU executes

Towards Automatic Video Annotation with ASH: Zero-Shot Open-Vocabulary Multi-Object Tracking and Segmentation

arXiv:2610.01022v1 Announce Type: new Abstract: Memory-attention-based Video Instance Segmentation (VIS) methods have demonstrated strong zero-shot tracking capability, yet their substantial memory re

Training-Free Diffusion Planning with Analytical Local Scores

arXiv:2610.01959v1 Announce Type: cross Abstract: Path finding and multi-robot motion planning require trajectories that are smooth, goal-directed, and collision-free in environments with complex geom

A Pre-trained Variational Autoencoder for Gyrokinetic Plasma Turbulence Surrogate Modeling

arXiv:2609.38438v1 Announce Type: cross Abstract: Machine learning surrogate models offer a promising path toward accelerating plasma turbulence simulations. We present PreVAE-Turb, a surrogate modeli

Bongard: Training Machine Intuition

arXiv:2609.39111v1 Announce Type: new Abstract: Human intelligence relies heavily on learned intuition: recognising patterns and judging situations without explicitly unfolding every intermediate step

hardwarearxiv-cs-cl

Data-Efficient Adaptation of a Driving VLA to Class 8 Trucks

arXiv:2609.38570v1 Announce Type: new Abstract: Class 8 trucks differ from passenger cars in geometry, dynamics, and maneuvering requirements. As a result, vision-language-action (VLA) models trained

Dense Temporal Motion Retargeting for Legged Robots

arXiv:2609.38617v1 Announce Type: new Abstract: Legged robots can learn expressive whole-body skills from the motions of humans and animals. Due to the morphology gap between the source and the robot,

EDGC: Entropy-driven Dynamic Gradient Compression for Efficient LLM Training

arXiv:2511.10333v2 Announce Type: replace-cross Abstract: Training large language models (LLMs) at scale incurs substantial communication overhead, while static gradient compression cannot adapt to gr

Efficient Expert-Parallel Communication on PCIe-Connected Consumer GPUs

arXiv:2609.40093v1 Announce Type: cross Abstract: Expert parallelism (EP) enables inference of large Mixture-of-Experts (MoE) models by placing their experts across multiple GPUs, but requires substan

FlashDiffusion: Fused Tiled Kernel Spectral Decomposition

arXiv:2609.38198v1 Announce Type: new Abstract: Diffusion maps, and kernel methods more generally, provide an interpretable nonlinear spectral representation basis for geometric learning. In the geome

Gestalt: a meta-foundation model for astronomy

arXiv:2609.38312v1 Announce Type: cross Abstract: The Platonic Representation Hypothesis predicts that sufficiently scaled foundation models converge on a shared representation of the world. As each n

GPU-Accelerated Path-Dependent Marginal Information Gain for Autonomous Exploration

arXiv:2609.40297v1 Announce Type: new Abstract: Autonomous exploration demands that robots continuously evaluate candidate viewpoints based on their expected information gain and execution cost. Sampl

MEMO: Multi-Level Entity-Aware Memory for Streaming Video Understanding

arXiv:2609.38900v1 Announce Type: new Abstract: Streaming video understanding requires models to process unbounded visual streams while preserving rich visual semantics across vast temporal horizons,

Onboard Vision and MPC Navigation for Underwater Robots: An Open BlueROV2 Platform for Multi-Robot Experiments & Docking

arXiv:2609.38511v1 Announce Type: new Abstract: Autonomous underwater robots require robust perception, estimation and control to operate in confined environments. This paper presents an open-source B

Model Releases

QATFactory: A Versatile, Deployment-Aligned Framework for Quantization-aware Training and Distillation of LLMs

model-releasesarxiv-cs-lg

arXiv:2609.39223v1 Announce Type: new Abstract: Large language model (LLM) inference is increasingly moving toward lower precision to realize the throughput of hardware accelerators, but aggressive po

Shared Phase and Retention Control for Efficient Adaptive Spectral Recurrence

arXiv:2609.39082v1 Announce Type: new Abstract: As new evidence arrives, a sequence model must update what it remembers and how memory influences predictions. While Transformers incur computation and

SparLeak: Privacy Leakage from Sparse Attention in LLM Inference on Shared GPUs

arXiv:2609.38830v1 Announce Type: new Abstract: Sparse attention is widely used to accelerate long-context inference in modern large language models (LLMs), but its input-dependent execution behavior

Sparse-WAM: Accelerating World Action Models via Action-Guided Sparse Imagination

arXiv:2609.38984v1 Announce Type: cross Abstract: World-action models (WAMs) leverage pretrained video models to improve generalization in robot control by jointly predicting future visual states and

When Masking Helps or Hurts Robustness in Compressed CLIP: A Pre-Deployment Diagnostic

arXiv:2609.39704v1 Announce Type: cross Abstract: This paper demonstrate that whether masking-based token pruning helps or hurts worst-group robustness can be predicted before deployment, without labe

AI as a Compiler: Compiling Triton kernels without the Triton compiler

arXiv:2609.36800v1 Announce Type: new Abstract: Compiler backends are expensive to build and maintain as programming models, workloads, and accelerators evolve. We investigate whether large language m

BASE: Batch-Aware Selection of Experts Using Predicted Removal Error for Efficient MoE Decoding

arXiv:2609.36222v1 Announce Type: new Abstract: Large language models are increasingly expensive to serve. In large-scale serving systems, autoregressive decoding is often bottlenecked by transferring

BiFE: Search-Efficient Discovery of CPU-Only Branching Policies via LLM-based Bi-Fidelity Evolution

arXiv:2609.36735v1 Announce Type: new Abstract: In branch-and-bound (B&B) for mixed-integer linear programming (MILP), branching variable selection critically impacts efficiency. Existing neural branc

DIET: Deletion-response Expert Trimming for Video Diffusion Transformers

arXiv:2609.37829v1 Announce Type: new Abstract: Video diffusion transformers (DiTs) increasingly adopt mixture-of-experts (MoE) architectures to reduce active computation, but their full expert storag

FastVR: Efficient Streaming Video Restoration with One-Step Diffusion

arXiv:2609.36757v1 Announce Type: new Abstract: Diffusion-based video restoration recovers realistic details, but its practical deployment is limited by two efficiency bottlenecks: costly VAE encoding

Federation of Experts: Communication Efficient Distributed Inference for Large Language Models

arXiv:2605.06206v2 Announce Type: replace Abstract: Mixture of experts has emerged as the primary mechanism for making Large Language Models (LLMs) computationally efficient. However, in distributed s

GEM-KMeans: Memory-Efficient and Accurate Clustering on Massive Scale with GPU Optimization

arXiv:2609.36074v1 Announce Type: new Abstract: Memory-efficient scaling on clustering problems without sacrificing statistical accuracy is of central interest for large-scale data analysis and machin

HelixWorld: A Real-time Interactive Audio-Visual World Model

arXiv:2609.38123v1 Announce Type: new Abstract: World simulation is inherently multisensory, demanding synchronized visual and acoustic dynamics in real time. Yet prevailing interactive world models r

Label Less, Learn More: Resource-Efficient Active Semi-Supervised Learning for Onboard Satellite Image Annotation

arXiv:2609.37481v1 Announce Type: new Abstract: Large-scale pervasive sensing increasingly relies on high-resolution satellite imagery, yet task-specific onboard vision is constrained by costly annota

One from Infinity: Actualizing Futures from Pretrained World Models into Robot Actions

arXiv:2609.36413v1 Announce Type: new Abstract: A pretrained video world model admits many plausible futures for a scene, but a robot must realize the exact task-conditioned one. To turn world models

Probe-Space Preconditioning for Fast and Stable Zero-Order Training

arXiv:2609.38095v1 Announce Type: new Abstract: Backpropagation (BP) dominates deep learning but imposes a massive memory tax. For example, training OPT-30B with Adam requires approx 600GB of GPU memo

RelayVSR: Large-Small Model Collaboration for Efficient Real-World Video Super-Resolution

arXiv:2609.37850v1 Announce Type: new Abstract: Large generative models can recover realistic detail in real-world video super-resolution (VSR), but processing an entire video with them is computation

STEPQuant: When and Where Errors Matter in Delta-Rule Recurrent State Quantization

arXiv:2609.38169v1 Announce Type: cross Abstract: Linear attention replaces growing KV caches with fixed-size recurrent states, yet these persistent states can become a substantial memory bottleneck u

Trident: Unifying Guarded Dispatch and Host Execution for PyTorch Triton Workloads

arXiv:2609.37241v1 Announce Type: new Abstract: User-written Triton kernels enable high-performance GPU computation within PyTorch, but their end-to-end latency can remain dominated by host-side orche

ADPTNet: Adaptive with Prescriptive Timescales Non-Linear SSM for Sequence Modelling

arXiv:2609.34034v1 Announce Type: cross Abstract: A central aim of neuromorphic computing is to provide a viable alternative to highly energy-intensive Transformer-based AI. However, efficient alterna

Model Releases

Autonomous Research Project Management as an Agent Skill: A Case Study in Exact Spectral Spatial Regression

model-releasesarxiv-cs-lg

arXiv:2609.31683v1 Announce Type: new Abstract: This work presents an end-to-end demonstration of autonomous machine learning research conducted by an agent skill on consumer hardware. The demonstrati

Does Execution Require Target KV Fidelity? A Mixed-Fidelity KV Runtime for LLM Serving

arXiv:2609.33536v1 Announce Type: new Abstract: Large language model (LLM) serving is increasingly constrained by the GPU memory consumed by key-value (KV) caches. Existing compression, eviction, and

Efficient World Action Model Inference with Adaptive Intermediate States

arXiv:2609.34608v1 Announce Type: new Abstract: World Action Models (WAMs) enable future-aware control by jointly modeling actions and environment dynamics. However, iterative diffusion or flow infere

Fill2SR: Repurposing Inpainting Diffusion Transformers for Real-World Super-Resolution

arXiv:2609.33582v1 Announce Type: new Abstract: Recent real-world image super-resolution (SR) methods often adapt text-to-image (T2I) backbones with ControlNet-style branches or spatial conditioning t

FLARE: Flow Matching with Local Axis-Angle Representations for Stochastic Micromagnetic Evolution

arXiv:2609.34070v1 Announce Type: new Abstract: Long-horizon micromagnetic simulation remains expensive because conventional and learned solvers typically propagate Landau--Lifshitz--Gilbert (LLG) dyn