Search: “deployment”

Matryoshka Hash Representations for Model-Aware Compact Semantic Retrieval

arXiv:2609.07276v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) depends on dense retrieval: each document is stored as a learned vector, and a query is answered by finding its n

researcharxiv-cs-lg

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Miles v0.1: Production-Level Post-Training

DGX agent

arXiv:2609.08368v1 Announce Type: new Abstract: We present Miles v0.1, a full-stack, production-ready system for frontier post-training. Building upon the clean design of slime, Miles designs each sta

model-releasesarxiv-cs-lg

9 Sept 2026

MobileVLA-R1 2.0: RL-Enhanced Reasoning for Mobile Robot Control

arXiv:2609.06251v1 Announce Type: new Abstract: Grounding natural-language instructions into reliable and executable actions remains a fundamental challenge for vision-language-action (VLA) systems on

safetyarxiv-cs-cv

MolParser-Mobile: Ultrafast OCSR System for Large-Scale Chemical Literature Mining

arXiv:2609.05807v1 Announce Type: new Abstract: Optical Chemical Structure Recognition (OCSR) is a fundamental component of chemical literature mining, enabling molecular database construction, reacti

hardwarearxiv-cs-cv

MORPHA: Morphology-Constrained Training and the Limits of Cross-Acquisition Transfer in Low-Resource Malaria Microscopy

arXiv:2609.05990v1 Announce Type: new Abstract: In low-resource malaria microscopy, a model trained on one smear preparation routinely meets images from another, and how well morphology-based constrai

Multi-robot Learning-based Informative Path Planning Using Spatio-Temporal Gaussian Process Kalman Filter

arXiv:2609.05515v1 Announce Type: new Abstract: Multi-robot informative path planning (IPP) for persistent target monitoring requires robots to reason about spatial uncertainty, temporal evolution, an

Multimodal Resource-Exhaustion Attacks on Vision-Language Models via Joint Pixel-Prompt Optimization

arXiv:2609.05889v1 Announce Type: cross Abstract: Resource-exhaustion attacks against autoregressive vision-language models (VLMs) typically assume unimodal threat models, treating the image branch as

Nice paper to improve inference efficiency. It's been a while we haven't seen good work on efficiency. Here is why it matters: A long-runnin…

Nice paper to improve inference efficiency. It's been a while we haven't seen good work on efficiency. Here is why it matters: A long-running agent's workspace outgrows its context window long before

model-releasesdair-ai--x

NSFlow: End-to-End Differentiable Neuro-Symbolic Optical Flow for Visual Odometry

arXiv:2609.06074v1 Announce Type: new Abstract: Sparse optical flow provides stable inter-frame correspondence, playing a key role in Visual Odometry (VO) and Visual-Inertial Odometry (VIO). Classical

Observe Before You Alert: Adaptive Driver Alerting with Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2609.08130v1 Announce Type: new Abstract: Driver alerting from dashcam video requires sequential decision-making under partial observability: a system must decide not only whether a scene is ris

One MLLM, One Call: Efficient Zero-Shot Vision-and-Language Navigation via Spatial-Aware Waypoints

arXiv:2609.06476v1 Announce Type: new Abstract: Vision-and-Language Navigation in Continuous Environments (VLN-CE) requires an embodied agent to navigate unseen environments by following natural langu

agentsarxiv-cs-cv

OpenWAM: An Open, Modular Exploration Towards Systematic World-Action Model Pretraining

arXiv:2609.07398v1 Announce Type: new Abstract: World-Action Models inherit world knowledge from video-generative priors, and channel it into executable control signals through embodied experience. Ex

applicationsarxiv-cs-ro

Local Ai

PCSDiff: Diffusion-Based Bias Correction and Super Resolution Toward Practical Operational Medium-Term Precipitation Forecast

arXiv:2609.06942v1 Announce Type: new Abstract: Medium-range precipitation forecasts are impaired by persistent systematic biases, lead-time-dependent error accumulation, and coarse spatial resolution

local-aiarxiv-cs-lg

PGMT: Perceptive General Motion Tracking for Humanoid Robots

arXiv:2609.08511v1 Announce Type: new Abstract: Humanoid motion trackers can reproduce diverse whole-body motions, but their performance degrades on complex terrain where terrain-agnostic references b

RAFM-SER++: A Lightweight Multimodal Emotion Recognition Framework for Real-Time Behavioral Monitoring in Surveillance Systems

arXiv:2609.07409v1 Announce Type: cross Abstract: Recent multimodal Speech Emotion Recognition (SER) systems achieve high accuracy through interaction-heavy cross-modal transformers, but their computa

safetyarxiv-cs-lg

Re-engineering SORT-based algorithms for low-cost small object tracking from omnidirectional footage

model-releasesarxiv-cs-cv

arXiv:2609.07547v1 Announce Type: new Abstract: Multi-object tracking (MOT) has advanced rapidly in urban surveillance and autonomous driving, yet many trackers rely on ReID- and transformer-based app

ReactVAU: A Slow-Fast Decoupled Framework for Streaming Video Anomaly Understanding

arXiv:2609.07941v1 Announce Type: new Abstract: In this paper, we propose ReactVAU, a Slow-Fast Decoupled Framework for real-time streaming Video Anomaly Understanding (VAU). Existing VAU methods rely

Real-time Puncture Detection and Recovery for Pneumatic Soft Actuators

arXiv:2609.08804v1 Announce Type: new Abstract: Soft robots offer safe and adaptive interaction with humans and unstructured environments through their inherent ability to deform and comply. Pneumatic

Remotely Detectable Keyed Communication through Motion

arXiv:2609.08920v1 Announce Type: new Abstract: Messages from electronic devices are conventionally received as text, audio, or radio signals. But robots move with rich, articulate motion in the real

ReST-RL: Reinforcing LLM Reasoning through Unified Self-Training and Value-Guided Search

arXiv:2508.19576v3 Announce Type: replace-cross Abstract: With respect to improving the reasoning accuracy of LLMs, the representative reinforcement learning (RL) method - Group Relative Policy Optimi

safetyarxiv-cs-lg

Rethinking Safety for Generalist Robots

arXiv:2609.06326v1 Announce Type: cross Abstract: Generalist robots promise to transform our society: the same system that prepares a meal or folds laundry might also repair a car, inspect infrastruct

RoboDreamer: Anticipatory Humanoid Locomotion with Predictive State-Space Models

arXiv:2609.07096v1 Announce Type: new Abstract: Humanoid locomotion requires control policies that remain stable under imperfect sensing while exploiting temporal context for consistent motion. We pre

Local Ai

SAM3-O2D2: Zero-Shot Object Out-of-Distribution Detection by Object Class Prompting of the SAM3-Image Model

arXiv:2609.08281v1 Announce Type: new Abstract: Object detectors have shown remarkable performance in various fields, among these medical imaging, surveillance, and autonomous driving. However, they a

local-aiarxiv-cs-cv

Scalability Analysis of Distributed Kolmogorov-Arnold Network Training on High-Performance Computing Systems

model-releasesarxiv-cs-lg

arXiv:2609.07740v1 Announce Type: cross Abstract: Kolmogorov-Arnold Networks (KANs) replace the fixed activation functions and linear weights of Multi-Layer Perceptrons (MLPs) with learnable univariat

Semi-Supervised Learning under Spatially Biased Sampling

model-releasesarxiv-cs-lg

arXiv:2609.07982v1 Announce Type: new Abstract: Standard semi-supervised learning (SSL) typically relies on labelled and unlabelled data sharing a common marginal distribution. This assumption is ofte

Simplify and support your TorchServe workloads using Ray Serve Deep Learning Containers

TorchServe is no longer maintained, leaving teams to own the entire GPU inference stack. The AWS Ray Serve Deep Learning Container is a supported, pre-tested container with the framework, GPU drivers,

hardwareaws-ml-blog

Situation Awareness for Intelligent Data Distribution in Connected Vehicles

arXiv:2609.05521v1 Announce Type: cross Abstract: The limitations of on-board sensors and blind spots caused by occlusion cause the reduction of perception quality in autonomous vehicles. In such case

agentsarxiv-cs-cv

Sparse Gain Radio Map Reconstruction With Geometry Priors and Uncertainty-Guided Measurement Selection

model-releasesarxiv-cs-cv

arXiv:2604.05788v2 Announce Type: replace Abstract: Radio maps are important for environment-aware wireless communication, network planning, and radio resource optimization. However, dense radio map c

Steering Under Compression: Dose-Response, Capability Cost, and Failure Asymmetry in Quantized LLMs

model-releasesarxiv-cs-lg

arXiv:2609.06473v1 Announce Type: new Abstract: Inference-time activation steering enables behavioral control of large language models without parameter modification, while post-training quantization

Stochastically Perturbed Weights: Ensembles from Deterministic Machine-Learning Weather Models

arXiv:2609.08412v1 Announce Type: new Abstract: Machine-learning weather models (MLWMs) now match or outperform operational numerical weather prediction (NWP) at global medium-range forecasting, at fa

applicationsarxiv-cs-lg

Strategic Doctrine Language Models (sdLM): A Learning-System Framework for Doctrinal Consistency and Geopolitical Forecasting

arXiv:2601.14862v2 Announce Type: replace Abstract: We introduce Strategic Doctrine Language Models (sdLM), a learning-system framework for multi-document strategic reasoning with doctrinal consistenc

researcharxiv-cs-lg

SyncWorld: Visual Calibration Enables World Models as Zero-Shot Simulators

arXiv:2609.09155v1 Announce Type: new Abstract: World models are increasingly used as policy-in-the-loop imagination environments, where reliable rollouts require fine-grained controllability with res

safetyarxiv-cs-cv

TANGO: Humanoid Navigation in Cluttered Environments with a Whole-Body Vision-Language-Action Model

arXiv:2609.09158v1 Announce Type: new Abstract: We study the problem of navigating cluttered indoor environments with a humanoid robot. Unlike conventional methods that model navigation as a 2D path p

applicationsarxiv-cs-ro

TaskGuard: Task-Conditioned Restoration Utility for Risk-Aware Object Detection

arXiv:2609.08011v1 Announce Type: new Abstract: Image restoration is commonly applied before object detection under adverse conditions, yet a visually improved image need not improve the downstream ta

TFTrack: A Template-Free Framework for Efficient 3D Point Cloud Tracking

arXiv:2609.07738v1 Announce Type: new Abstract: LiDAR-based 3D Single Object Tracking (3D SOT) is critical for robotic perception and navigation and aims to localize dynamic objects across frames in s

safetyarxiv-cs-cv

The case for boycotting Generative AI: https://garymarcus.substack.com/p/the-case-for-boycotting-generative

Gary Marcus argues that current generative‑AI models fail to meet basic standards of reliability because they routinely hallucinate facts, amplify existing biases, and provide no transparent audit tra

safetygary-marcus--x

Tracking-by-detection in Multi-object Tracking: Survey and Experiments

arXiv:2609.08265v1 Announce Type: new Abstract: Multi-object tracking (MOT) is an essential computer vision task that simultaneously tracks multiple objects in video sequences, with various applicatio

agentsarxiv-cs-cv

TrojanWorld: Backdooring World-Model Agents via Imagination Steering

arXiv:2609.07051v1 Announce Type: new Abstract: World models increasingly serve as the predictive core of model-based reinforcement learning agents, enabling them to simulate future dynamics and reaso

agentsarxiv-cs-lg

Uni-Light: An Ultra-Lightweight Framework via Uncertainty-Aware Knowledge Distillation for Brain Tumour Segmentation

arXiv:2609.06729v1 Announce Type: new Abstract: Accurate 3D brain tumour segmentation from multi-modal Magnetic Resonance Imaging (MRI) is essential for clinical diagnosis and treatment planning. Exis

Unified Multi-Layer Subspace Modeling for Cross-Domain OOD Detection

arXiv:2609.06785v1 Announce Type: new Abstract: Out-of-Distribution (OOD) detection remains a fundamental challenge for neural networks, whose predictions can be overconfident on inputs that deviate f

applicationsarxiv-cs-cv

When to Use Encode-Prefill-Decode Disaggregation to Accelerate Multimodal Model Serving

Encode‑Prefill‑Decode (EPD) disaggregation is an inference optimization in NVIDIA Dynamo that separates vision encoding from LLM prefill–decode stages for multimodal requests. On image‑heavy prompts,

hardwarenvidia-developer

WM-Craftnet: World Synesthesia Model for Generalizable and Robust Dexterous In-Hand Manipulation

arXiv:2609.07002v1 Announce Type: new Abstract: Generalizable and robust dexterous in-hand manipulation requires a policy to infer object pose, geometry, contact, and potential slip from partial and n

Zero-Shot Sim-to-Real Contact-Rich Assembly via Proprioception-Anchored Cross-Modal Pretraining

arXiv:2609.07534v1 Announce Type: new Abstract: Contact-rich assembly remains challenging because it requires submillimeter spatial accuracy and reliable interpretation of forces during sustained cont

China says its AI compute capacity rose 177% YoY to 2,185 eflops by the end of June, and is targeting 9,800 eflops by 2030 via ~$532B in IT infrastructure spend (Howard Liu/South China Morning Post)

Howard Liu / South China Morning Post: China says its AI compute capacity rose 177% YoY to 2,185 eflops by the end of June, and is targeting 9,800 eflops by 2030 via ~$532B in IT infrastructure spend

safetytechmeme

How HPE Zerto built an agentic troubleshooting system with Amazon Bedrock

HPE Zerto built an agentic troubleshooting system powered by Amazon Bedrock that runs on-premises inside the customer environment. This post describes the multi-agent architecture, the on-premises dep

agentsaws-ml-blog

Introducing CUDA Rust: Two Tracks for Writing GPU Kernels

NVIDIA introduced two Rust projects for GPU development in September 2026: `cuda‑oxide`, a nightly‑only backend that compiles SIMT‑style kernels to PTX via LLVM and uses DisjointSlice and launch contr

hardwarenvidia-developer

Led by @Samsung, co-led by @eqt's Scaleup Europe Fund and @PSG_equity, with continued backing from @ASMLcompany, @nvidia, @BNPParibas CIB an…

Led by @Samsung, co-led by @eqt's Scaleup Europe Fund and @PSG_equity, with continued backing from @ASMLcompany, @nvidia, @BNPParibas CIB and others. This fuels our infrastructure and product capabili

hardwaremistral-ai--x

Nice report on agents beyond code generation. Here is why it matters: Coding agents raise how much code gets written. This report argues the…

Nice report on agents beyond code generation. Here is why it matters: Coding agents raise how much code gets written. This report argues the gains shrink sharply between writing code and shipping reli

model-releasesdair-ai--x