Search: “deployment”

arXiv:2609.22107v1 Announce Type: cross Abstract: Making prediction with multimodal data is widely used in diverse scenarios. Existing multimodal fusion models, once deployed, can only handle predefin

applicationsarxiv-cs-cl

Global Ranks Survive, Selected Heads Shift: BOS-Sink Topology under 4-bit Weight-Only Quantization

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DGX agent

arXiv:2609.23585v1 Announce Type: cross Abstract: Sink-aware deployment may identify important first-token attention heads before a model is quantized, then reuse that map at the edge. We test when th

model-releasesarxiv-cs-cl

22 Sept 2026

Harness-Zero: Harness Distillation via Agent-as-Harness

arXiv:2609.24974v1 Announce Type: cross Abstract: Agent harnesses, the external systems that mediate model-environment interaction, can substantially improve agent performance, but their gains remain

agentsarxiv-cs-cl

Introducing DigitalOcean Managed Agents: One AI-native stack to power your intelligence

model-releasesdigitalocean

Following a successful private preview, we’re thrilled to open DigitalOcean Managed Agents to everyone. Teams can now deploy their preferred agent harness (like OpenCode, Codex CLI) or bring their own

MIGU: Multimodal Instruction Grounding under Uncertainty for Manipulation Planning

model-releasesarxiv-cs-ro

arXiv:2609.24995v1 Announce Type: new Abstract: Understanding natural human instructions is crucial for deploying robots in human-centric environments. We study multimodal instruction grounding, where

MIRA: Real-Time Full-Duplex Human-Robot Interaction for Embodied Companions

arXiv:2609.24547v1 Announce Type: new Abstract: Real-time embodied companion interaction requires a robot to infer user intent from streaming speech, generate timely responses, and execute expressive,

Physical-Touch Observability from Wrist Wrench in Granular Scooping

arXiv:2609.22852v1 Announce Type: new Abstract: Mining and earthmoving are important real-world deployment settings for embodied intelligence. Autonomous transport and driving systems have improved su

agentsarxiv-cs-ro

PRIMO: Prior-Informed Odometry from Human-Motion Tracking for Humanoid Robots

arXiv:2609.23610v1 Announce Type: new Abstract: Simulation-trained humanoid proprioceptive odometry faces two transfer challenges: training trajectories generated by specific robot control policies in

Industry

Right-size generative AI endpoints with concurrency sweeps on Amazon SageMaker AI

Concurrency sweeps help you right-size a generative AI endpoint on Amazon SageMaker AI by systematically benchmarking it at increasing load levels. This post walks through deploying a model, running a

industryaws-ml-blog

SAFe: Segment-guided Aggregation of Feature Densities for Anomaly-aware Segmentation

model-releasesarxiv-cs-cv

arXiv:2609.24204v1 Announce Type: new Abstract: Visual segmentation systems encounter objects outside their training distribution during real-world deployment, hindering reliable autonomous systems th

SCALE: Simulation-Calibrated Amortized Learning for Energy Materials (A hybrid architecture connecting deterministic modeling, real-world data, and transformer-scale inference for accelerated energy-materials discovery)

arXiv:2609.22233v1 Announce Type: new Abstract: Energy systems face converging pressures for security, affordability, resilience, and sustainability, creating a need for faster discovery of deployable

local-aiarxiv-cs-lg

Semi-automated reconstruction of indoor geometry from 360-degree video for CFD-based airflow analysis in classrooms

model-releasesarxiv-cs-cv

arXiv:2609.23425v1 Announce Type: new Abstract: Computational Fluid Dynamics (CFD) is widely used to evaluate ventilation and contaminant transport in occupied buildings, but deployment at scale is li

Smoothness as a Constraint for Stable Humanoid Locomotion

arXiv:2609.24552v1 Announce Type: new Abstract: Embodied AI systems, particularly humanoid robots deployed in real world scenarios require whole-body control policies that are both task-responsive and

SPACE: Semantic Projection and Alignment of CLIP Embeddings for Domain Adaptation

arXiv:2609.23248v1 Announce Type: new Abstract: A fundamental challenge in deploying vision models is domain shift, which arises when training and test data follow different distributions, leading to

safetyarxiv-cs-cv

Stability-Aligned Residual Adaptation for Rapid Recovery from Dynamics Shifts

arXiv:2603.07775v2 Announce Type: replace Abstract: Robotic systems deployed beyond controlled environments encounter abrupt and unobserved dynamics shifts that induce substantial transient performanc

local-aiarxiv-cs-ro

The Role of Dataset Linguistic Structure in the Cultural Awareness of Large Language Models

model-releasesarxiv-cs-cl

arXiv:2602.01161v2 Announce Type: replace Abstract: The global deployment of large language models (LLMs) has raised concerns about cultural misalignment, yet the linguistic properties of fine-tuning

Toward Mission-Critical ISAC: Reliable Energy-Aware Coordination in UAV Swarms

arXiv:2609.22292v1 Announce Type: cross Abstract: Unmanned aerial vehicle (UAV) swarms deployed in mission-critical applications must simultaneously track a mobile aerial target and maintain reliable

agentsarxiv-cs-ro

Transferring Visual Explanations: How Cross-Architecture Knowledge Distillation Affects Model Interpretability

arXiv:2609.23561v1 Announce Type: new Abstract: Deploying efficient neural networks is essential in resource-constrained environments, yet compact models often sacrifice interpretability - a critical

local-aiarxiv-cs-cv

Validating, Not Sampling: Region-Level Robustness of Vision-Language and Vision-Language-Action Models

model-releasesarxiv-cs-cv

arXiv:2609.22293v1 Announce Type: new Abstract: Vision-language models (VLMs) and vision-language-action models (VLAs) are increasingly deployed in real-world applications. There, a small perturbation

When Quantization Preserves Accuracy but Not Evidence: Explanation-Aware Post-Training Quantization for Medical LLMs

arXiv:2609.24799v1 Announce Type: new Abstract: Post-training quantization (PTQ) enables efficient deployment of large language models, and PTQ methods are usually optimized and evaluated with generic

researcharxiv-cs-cl

WPBench: A Comprehensive Benchmark for Wind Power Forecasting

model-releasesarxiv-cs-lg

arXiv:2609.24444v1 Announce Type: new Abstract: Accurate, reliable, and deployable wind power forecasting is critical for power system dispatch, renewable energy integration, and electricity market op

A Novel Path-Tracking Algorithm for Automated Tractor-Trailer Forward and Backward Maneuvers

arXiv:2609.21718v1 Announce Type: new Abstract: Fully autonomous tractor--trailer systems are increasingly deployed in logistics, agriculture, and industrial environments, where precise and robust pat

agentsarxiv-cs-ro

AirSplan: Risk-Aware Motion Planning for Quadrotors in Cluttered 3D Gaussian Splats

arXiv:2609.21226v1 Announce Type: new Abstract: Quadrotors are increasingly deployed in applications such as agriculture, infrastructure inspection, and maintenance. In each of these applications, the

DENSE: Distilling Agent Trajectories into Evidence-Grounded Shortcut Trees for Self-Refinement

arXiv:2609.21423v1 Announce Type: new Abstract: Online agent deployments produce abundant execution traces, while task-specific verification and expert annotation are costly to scale. We study how to

Diffusion-Based Tumor Inpainting for Renal Segmentation under Clinical Data Scarcity

arXiv:2609.21698v1 Announce Type: new Abstract: Deep learning segmentation of renal tumors requires large annotated datasets, yet clinical deployments typically offer only a handful of tumor-positive

researcharxiv-cs-cv

Duty Factor Predicts Robust Constrained Quadrupedal Locomotion Across Gait Types

model-releasesarxiv-cs-ro

arXiv:2609.22073v1 Announce Type: new Abstract: Quadrupedal robots are increasingly deployed in environments where locomotion must remain robust to disturbances and constrained terrain. Gait type, suc

Efficient Benchmarking in Production: A Study of an Evolving LLM Agent

arXiv:2609.21267v1 Announce Type: new Abstract: Production LLM agents are evaluated repeatedly as they evolve, but full agent benchmarks are costly to rerun. We study efficient recurring evaluation fo

Geometry of Values: Task Vector Composition for Ethical Preference Alignment in Language Models

arXiv:2609.21094v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly deployed in applications that must weigh clashing moral values, yet even strong models exhibit hidden bi

LittleHorse adds agent controls and free serverless trial to its ‘Business-as-Code’ orchestration platform

LittleHorse Enterprises LLC, a maker of workflow orchestration software spanning multiple applications, today announced version 1.3 of its Saddle Command Center, adding no-code agent deployment, prebu

agentssiliconangle

NVIDIA Launches DSX Ready to Qualify Power and Cooling Products for AI Factories

model-releasesnvidia-blog

Every AI factory needs power and cooling that fit its computing architecture. As AI infrastructure expands, power, cooling, water, site and grid constraints are shaping what builders can deploy. Choos

One Prompt Does Not Fit All: Self-Meta-Evolve for Personalized Information Extraction

arXiv:2609.21626v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed for enterprise information extraction (IE), where the same document must be reorganized different

Quantization-Aware Kalman Estimation for Diffusion Sampling

arXiv:2609.21407v1 Announce Type: new Abstract: Quantization offers a practical path to deploying diffusion models with reduced memory and computation, but aggressive compression can cause quantized o

local-aiarxiv-cs-cv

Safe Real-Time Policy Steering via Noise-Space Trajectory Optimization for One-Step Generative Policies

arXiv:2609.21220v1 Announce Type: new Abstract: Generative robot policies can represent diverse, multimodal behaviors, but adapting pretrained policies to deployment-time constraints such as collision

Semantic Calibration Prevails Where Token Confidence Fails: Benchmarking Long-Form Scientific QA

model-releasesarxiv-cs-cl

arXiv:2602.00279v2 Announce Type: replace Abstract: Reliable uncertainty quantification (UQ) is essential for safe deployment of large language models (LLMs) in scientific question answering, where lo

Taming the Adversary: A Cost-to-Disturbance Ratio Approach to Adversarial Reinforcement Learning

arXiv:2603.12110v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) policies trained in simulation often degrade once deployed on real systems, where the controller must reject exter

TERMon: Detecting Persistent Behavioral Threats in Edge AI via Hardware-Native Ternary Runtime Monitor

arXiv:2609.21713v1 Announce Type: cross Abstract: Edge AI accelerators are increasingly deployed in safety-critical environments, where model outputs may control physical actuators, make access-contro

local-aiarxiv-cs-ai

Watermarkable Multi-Draft Speculative Sampling via Poisson Processes

arXiv:2609.21858v1 Announce Type: cross Abstract: Large language models (LLMs) have achieved state-of-the-art performance across a wide range of tasks, motivating two important aspects of deployment:

researcharxiv-cs-lg

Amazon SageMaker Inference: 2026 year-to-date launches in review

model-releasesaws-ml-blog

Amazon SageMaker AI shipped 13 inference launches in the first half of 2026 across two deployment paths: fully managed endpoints and Amazon SageMaker HyperPod Inference. This post reviews each launch,

Distance to Class Prototypes: Active Learning for Object Detection

arXiv:2609.20248v1 Announce Type: new Abstract: Deploying a deep object detector in a new setting is limited less by architecture than by the cost of annotating data from that setting. Active learning

researcharxiv-cs-cv

Emergent interactions lead to collective frustration in robotic matter

arXiv:2507.22148v3 Announce Type: replace-cross Abstract: Artificial intelligence and robotic systems are increasingly deployed as interacting collectives of learning agents. This raises the question

researcharxiv-cs-ro

Applications

Enhanced Knowledge Distillation for Detection Transformer via Teacher Prediction Refinement

arXiv:2609.19964v1 Announce Type: new Abstract: Detection Transformers (DETRs) achieve strong performance in object detection but remain challenging to deploy on edge devices due to their high computa

applicationsarxiv-cs-cv

F^{2}DR: A Fine-Grained Full-Pipeline Reward Framework for DeepSearch Workflows

model-releasesarxiv-cs-cl

arXiv:2609.19827v1 Announce Type: new Abstract: With the widespread industrial deployment of Large Language Models (LLMs), DeepSearch has emerged as the dominant paradigm for resolving complex user qu

Industry

Full speed ahead: Despite calls to slow AI down, its support structure is on the fast track

While tech titans at Salesforce Inc.’s Dreamforce event in San Francisco this week engaged in a spirited debate over whether the pace of deployment for artificial intelligence should be slowed, a grou

industrysiliconangle

GeLaCo: An Evolutionary Approach to Layer Compression

arXiv:2507.10059v2 Announce Type: replace Abstract: Large Language Models have achieved remarkable performance across a large number of tasks, but face critical deployment and usage barriers due to su

local-aiarxiv-cs-cl

Governance-as-Code: Translating EU AI Act Technical Requirements into Executable Compliance Pipelines for Generative AI Systems

arXiv:2609.20016v1 Announce Type: cross Abstract: The EU AI Act (Regulation 2024/1689) imposes technical obligations on high-risk AI providers, yet Articles 8-15 were drafted for predictive AI and lea

safetyarxiv-cs-ai

Local Sparsity Enables Unsupervised LLM Safety Detection

arXiv:2609.20129v1 Announce Type: cross Abstract: Deployment-time safety methods for large language models (LLMs) are predominantly supervised and assume access to unsafe training data. Nevertheless,

local-aiarxiv-cs-ai

Open ultrasound foundation model for robust segmentation and clinical measurement across heterogeneous settings

arXiv:2609.19230v1 Announce Type: new Abstract: Ultrasound is the most widely deployed imaging modality worldwide, yet clinical AI remains fragmented into narrow single-task models that fail when devi

researcharxiv-cs-cv

Opinion Dynamics-based Coalition Formation for Federated Learning in Heterogeneous IoT Systems

arXiv:2609.19695v1 Announce Type: new Abstract: Federated learning (FL) enables privacy-preserving, on-device training across heterogeneous Internet-of-Things (IoT) deployments such as smart-city wate

local-aiarxiv-cs-lg