Search: “deployment”

arXiv:2610.16863v1 Announce Type: cross Abstract: Organizations pairing a human and a machine on a task decide, often by default, which executes each instance and what happens when both do. We account

tutorialsarxiv-cs-lg

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Beyond Fixed Visual History: Learning Motion-Adaptive Temporal Receptive Fields for Complex-Terrain Quadruped Locomotion

DGX agent

arXiv:2610.14753v1 Announce Type: new Abstract: Versatile quadruped locomotion depends on a tight coupling between what the robot perceives and what its body can execute. Yet existing visual controlle

safetyarxiv-cs-ro

14 Oct 2026

Agents

BREAKING: SpaceXSI just revealed that Starlink uses Grok Voice 3.0 to handle 20,000 daily calls in multiple languages. About 70% need no hum…

BREAKING: SpaceXSI just revealed that Starlink uses Grok Voice 3.0 to handle 20,000 daily calls in multiple languages. About 70% need no human & 1 in 4 sales calls ends in a purchase. AI agent verifie

agentselon-musk--x

BridgeCodec: Mamba Enhanced Neural Audio Codec with Schrodinger Bridge at Low Bitrate

arXiv:2610.15453v1 Announce Type: cross Abstract: Neural audio codecs achieve remarkable performance but operate as closed ecosystems with rigidly co-trained encoderdecoder pairs, severely hindering i

C2Flight: A Closed-Loop Co-Simulation Framework for Early-Stage Evaluation of Heterogeneous UAV Computing Systems

arXiv:2610.14715v1 Announce Type: new Abstract: Early-stage design of heterogeneous UAV computing systems requires evaluating how algorithm, hardware, communication, and system topology affect closed-

CALM-5G: Event-Level Conformal Risk Control for Predictive Service-Assurance Alarms

arXiv:2610.17962v1 Announce Type: cross Abstract: Predictive service assurance converts forecasts of key performance indicators into alarms, and that conversion decides whether the assurance function

applicationsarxiv-cs-lg

Chunk-wise Model-based Policy Optimization

arXiv:2610.14564v1 Announce Type: cross Abstract: Model-based reinforcement learning has shown superior sample efficiency by leveraging the learned latent dynamics either in the form of derivative-fre

safetyarxiv-cs-lg

Coarse-Graining Recursive Expert Computation: Continuation-Relative Interfaces and Failure Modes

arXiv:2610.14413v1 Announce Type: new Abstract: Computational coarse-graining aims to replace a sequence of updates with a cheaper module while preserving task performance. We present a continuation-r

Competitive Task Allocation with Temporal Proposal Windows and Improved Artificial Potential Fields for Dual-Arm Industrial Manipulation

arXiv:2610.15763v1 Announce Type: new Abstract: Modern industrial automation demands autonomous collaborative systems capable of coordinated manipulation in workspaces with heterogeneous object arrang

Compositional Average Velocity Modeling for Efficient Diffusion Offline Reinforcement Learning

arXiv:2610.14941v1 Announce Type: new Abstract: Diffusion-based policies have recently emerged as a powerful paradigm for offline reinforcement learning, but their reliance on multi-step denoising int

safetyarxiv-cs-lg

CopyQuad: Quadrupedal Skill Transfer from a Single Side-View Video Without a Depth Model

arXiv:2610.16737v1 Announce Type: cross Abstract: Video-to-robot pipelines for quadrupedal imitation insert a learned lifting stage, either a monocular depth model or a per-clip 3D reconstruction, to

D^{2}-VPR: A Parameter-efficient Visual-foundation-model-based Visual Place Recognition Method via Knowledge Distillation and Deformable Aggregation

model-releasesarxiv-cs-cv

arXiv:2511.12528v5 Announce Type: replace Abstract: Visual Place Recognition (VPR) aims to determine the geographic location of a query image by retrieving its most visually similar counterpart from a

Data-Free Continual Learning for World Action Model with Rectified Generative Replay

arXiv:2610.18038v1 Announce Type: cross Abstract: World action models (WAMs) built on pretrained video generation models adapt quickly to new robotic tasks, but they forget previously learned tasks un

Deeply unrolled alternating projections for phase retrieval

arXiv:2610.17316v1 Announce Type: cross Abstract: Deep unrolling methods for inverse problems augment traditional reconstruction algorithms with learned priors to improve their performance. These meth

Hardware

Denoise X: Self-Supervised U-Net for Quantum Mottle Suppression in Chest Radiography

arXiv:2610.18556v1 Announce Type: new Abstract: Deep learning for medical image restoration is often constrained by the need for paired training data. Acquiring perfectly registered clean-noisy radiog

hardwarearxiv-cs-cv

Design and Evaluation of a Collaborative Teleoperation Interface for Multi-Operator Multi-Robot Systems in Challenging Environments

arXiv:2610.15001v1 Announce Type: new Abstract: Multi-robot systems that combine the complementary capabilities of specialised platforms are critical for complex missions in challenging, inaccessible

Detecting Unreliable Classifications from Quantized Models

arXiv:2610.18575v1 Announce Type: new Abstract: Post-training INT8 quantization is typically validated by checking accuracy retention, which requires ground-truth labels often unavailable in low-resou

researcharxiv-cs-cv

Disentangling Marginal Capacity from Geometry in Optimal-Transport Label Transfer

arXiv:2610.14853v1 Announce Type: new Abstract: Optimal transport (OT) is widely used to align distributions and transfer labels between unpaired source and target data, but source-target composition

Distill3R: A Pipeline for Democratizing 3D Foundation Models on Commodity Hardware

model-releasesarxiv-cs-cv

arXiv:2602.00865v2 Announce Type: replace Abstract: While multi-view 3D reconstruction has shifted toward large-scale foundation models capable of inferring globally consistent geometry, their relianc

DPOison-VL: Clean Preference Poisoning in Vision-Language Direct Preference Optimization

arXiv:2610.18609v1 Announce Type: cross Abstract: Direct Preference Optimization (DPO) has become a widely adopted approach for aligning vision-language models (VLMs), yet the security of multimodal p

DRanker: A Transformer-Based Multi-Task Ranking Model for the Disney+ Homepage

arXiv:2610.15696v1 Announce Type: new Abstract: We present DRanker (Disney+ Ranker), a transformer-based multitask ranking model serving personalized recommendations on the Disney+ homepage. We descri

applicationsarxiv-cs-lg

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments

arXiv:2607.17291v2 Announce Type: replace Abstract: Deep research agents increasingly operate over the open web, where relevant records coexist with redundant summaries, outdated reports, and misleadi

Dynamic Interpolation for Training-Time Prediction Reshaping in Low-Light Image Enhancement

model-releasesarxiv-cs-cv

arXiv:2610.18018v1 Announce Type: new Abstract: Low-light image enhancement (LLIE) is an important image/video processing problem for reliable visual systems under poor illumination, yet it remains ch

Edge-Native Temporal--Graph Dual-Expert Inference for Dexterous Grasp Classification

arXiv:2610.14926v1 Announce Type: new Abstract: Multi-finger hands contact objects at different times, so a global close command can overload early-contact fingers while others are still moving. Dense

EgoAlign: Situated 3D Understanding without Situation Descriptions

arXiv:2610.16176v1 Announce Type: new Abstract: Situated 3D Question Answering requires models to interpret a 3D scene relative to an agent's pose. Existing methods commonly convey that pose through a

EgoCPT: Learning Dexterous Manipulation from a Single Ego-Centric Video with Contact-Aware Optimization

arXiv:2610.17572v1 Announce Type: new Abstract: While expert demonstrations on real robots are difficult to collect, human ego-centric videos are easy to collect and abundant on the internet. However,

Agents

EvolvAttack: Backdooring self Evolving VLM Agents

arXiv:2610.15244v1 Announce Type: new Abstract: Self-evolving mechanisms let vision-language model (VLM) agents continually adapt through evolving memory, but they also allow malicious behavior to eme

agentsarxiv-cs-lg

FETALFusion: Resolution-Aware State-Space Modeling for Multi-Domain Fetal Head Segmentation

arXiv:2610.17951v1 Announce Type: new Abstract: Head circumference (HC) measured from 2D ultrasound is a routine marker of fetal growth, and automating it needs segmentations whose boundaries hold up

researcharxiv-cs-cv

Fizgig 8 is out - A web UI finally! One app for your PC, your other PCs, and RunPod

model-releasesr-stablediffusion

Every PC, one app. Fizgig finds your other computers on your network by itself. Train on the desktop's 5090 from your laptop, send a dataset across in one click, and see what every machine is training

Flow-Support-Weighted Proposals for Test-Time Verified VLA Policies

arXiv:2610.14588v1 Announce Type: cross Abstract: Test-time sampling promises to turn one action prediction into a set of distinct executable candidates that a verifier can choose among. Downstream fi

Hardware

Force Sensor-Based Picking Pattern Analysis and Two-Jaw Gripper Design for Cherry Tomato Robotic Harvesting in Greenhouse

arXiv:2610.18160v1 Announce Type: new Abstract: Robotic harvesting of cherry tomatoes in greenhouses remains challenging due to dense fruit clusters, delicate skin, and the need for gentle yet effecti

hardwarearxiv-cs-ro

Local Ai

ForceWAM: Decoupling Future and Response Learning from Demo and Play Data for Contact-Rich Manipulation

arXiv:2610.18852v1 Announce Type: new Abstract: Expert demonstrations show how to complete contact-rich tasks, but provide limited coverage of how interaction forces respond to different actions. Task

local-aiarxiv-cs-ro

ForeTac: Predictive Contact Guidance for Generative Robot Policies

arXiv:2610.18118v1 Announce Type: new Abstract: Visually similar actions can produce contact loss, jamming, slippage, or irreversible damage, while tactile feedback may arrive after a critical transit

From a Large-Scale Teacher to Efficient Multimodal Students for Search Relevance Prediction

arXiv:2610.16569v1 Announce Type: cross Abstract: Relevance prediction between user queries and items is a fundamental component of e-commerce search systems. Traditionally, high-quality relevance lab

applicationsarxiv-cs-lg

From Rainfall to Road-Network Functionality: Transferable Graph Forecasting for Flood-Disrupted Transportation Networks

arXiv:2610.14622v1 Announce Type: new Abstract: Extreme rainfall can rapidly degrade road-network functionality (RNF), disrupting emergency mobility, accessibility, evacuation, logistics, and infrastr

From Video to Vision: Learning Generalizable Humanoid Carrying from Human Motion

arXiv:2610.14561v1 Announce Type: new Abstract: Most existing approaches rely on video or motion-capture data for reinforcement learning (RL) training; however, all of these methods require an upper-l

Local Ai

G^2WAM: World Action Models for Efficient and Geometry Grounded Image-Goal Navigation

arXiv:2610.16558v1 Announce Type: cross Abstract: World models capture environment dynamics and support counterfactual reasoning for planning. In image-goal navigation, where the target often lies bey

local-aiarxiv-cs-ro

GA-SVD: Generation-aware Singular Value Decomposition for LLM Compression

arXiv:2610.15398v1 Announce Type: new Abstract: Large language models (LLMs) demonstrate strong generalization across a broad range of reasoning and generation tasks, but their large parameter counts

GG-Nav: Goal-oriented Grounding Chain-of-Thought Elicits Reasoning in Navigation Foundation Models

arXiv:2610.14541v1 Announce Type: new Abstract: Emerging strong Vision-Language Models (VLMs) have advanced navigation foundation models. However, these models still have unsatisfactory performance on

applicationsarxiv-cs-ro

Harness^2: Recursive Agent Harnessing for an Open World

arXiv:2610.14224v1 Announce Type: cross Abstract: LLM agents' capabilities depend not only on their underlying models but also on their execution harnesses. Recursive self-improvement (RSI) offers a p

HGA-Quant: Heterogeneity-Aware Quantization for AutoRegressive Visual Generation Models

arXiv:2610.15297v1 Announce Type: new Abstract: Recently, AutoRegressive Visual Generation (ARVG) models have emerged as a competitive paradigm for high-quality image synthesis. However, their substan

applicationsarxiv-cs-cv

HierarchiRetina: A Diabetic Retinopathy Screening and Grading Cascade with Heterogeneous Mixture-of-Experts Lesion Segmentation

arXiv:2610.17933v1 Announce Type: new Abstract: Clinical screening for diabetic retinopathy proceeds in stages, yet most automated systems grade fundus images with a single black-box network. Three ga

researcharxiv-cs-cv

History, Adaptation, and Hidden Gain: Two Prospective Tests of Learned Predictive Control in a Synthetic Neural Population

arXiv:2610.14368v1 Announce Type: new Abstract: We study learned one-step predictive control of a synthetic population of 64 leaky integrate-and-fire neurons whose light sensitivity is scaled by a hid

How Low Can You Go: Fine-Tuning LLMs with Bayesian Optimization (LlMBO)

arXiv:2610.18504v1 Announce Type: cross Abstract: Recently, Morris et al. introduced TinyLoRA, a strategy for LLM fine-tuning which introduces arbitrarily few parameters, and demonstrated accuracy imp

Inference on the Value of Policy Improvement in Adaptive Experiments

arXiv:2610.15789v1 Announce Type: cross Abstract: In this paper, we develop an asymptotically normal estimator for the value of policy improvement (VPI) under adaptively collected data. This value, wh

safetyarxiv-cs-lg

Interpretable Graph Partitioning for Spatial Prediction

arXiv:2610.16063v1 Announce Type: new Abstract: Spatial prediction estimates unobserved values from spatially distributed observations. Although flexible predictive models are increasingly available,

LatentRiskBench: Measuring State-Dependent Risks in Enterprise Agents

arXiv:2610.17685v1 Announce Type: cross Abstract: Enterprise agents face safety risks that cannot be determined from individual actions alone. Existing safety benchmarks largely evaluate action-local

Learning Robot Policies for Whole-Body Mobility Assistance via Dynamic Human Motion Generation

arXiv:2610.17750v1 Announce Type: new Abstract: Robotic assistance for human mobility could benefit care recipients and reduce caregiver burden during physically demanding tasks such as Sit-to-Stand (