Search: “deployment”

Measuring What Matters: Benchmarking Generative, Multimodal, and Agentic AI in Healthcare

model-releasesarxiv-cs-ai

arXiv:2605.08445v1 Announce Type: new Abstract: AI models are increasingly deployed in live clinical environments where they must perform reliably across complex, high-stakes workflows that standard t

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Model Releases

MemPrivacy: Privacy-Preserving Personalized Memory Management for Edge-Cloud Agents

DGX agent

arXiv:2605.09530v1 Announce Type: cross Abstract: As LLM-powered agents are increasingly deployed in edge-cloud environments, personalized memory has become a key enabler of long-term adaptation and u

model-releasesarxiv-cs-cl

12 May 2026

Navigating the Sea of LLM Evaluation: Investigating Bias in Toxicity Benchmarks

model-releasesarxiv-cs-ai

arXiv:2605.10639v1 Announce Type: new Abstract: The rapid adoption of LLMs in both research and industry highlights the challenges of deploying them safely and reveals a gap in the systematic evaluati

ORICF -- Open Robotics Inference and Control Framework

arXiv:2605.09656v1 Announce Type: new Abstract: Recent advances in artificial intelligence (AI) have enabled effective perception and language models for robots, but their deployment remains computati

researcharxiv-cs-ro

Plan2Cleanse: Test-Time Backdoor Defense via Monte-Carlo Planning in Deep Reinforcement Learning

arXiv:2605.09638v1 Announce Type: new Abstract: Ensuring the security of reinforcement learning (RL) models is critical, particularly when they are trained by third parties and deployed in real-world

Security Risks in Tool-Enabled AI Agents: A Systematic Analysis of Privileged Execution Environments

arXiv:2605.09721v1 Announce Type: cross Abstract: Tool-enabled AI agents are increasingly deployed in cloud-hosted environments and offered as services, where they perform side-effecting operations th

agentsarxiv-cs-ai

SkillMAS: Skill Co-Evolution with LLM-based Multi-Agent System

arXiv:2605.09341v1 Announce Type: cross Abstract: Large language model (LLM) agent systems are increasingly expected to improve after deployment, but existing work often decouples two adaptation targe

agentsarxiv-cs-cl

SPECTRE: Hybrid Ordinary-Parallel Speculative Serving for Resource-Efficient LLM Inference

arXiv:2605.08151v1 Announce Type: cross Abstract: LLM serving platforms are increasingly deployed as multi-model cloud systems, where user demand is often long-tailed: a few popular large models recei

applicationsarxiv-cs-ai

The Agent Use of Agent Beings: Agent Cybernetics Is the Missing Science of Foundation Agents

arXiv:2605.10754v1 Announce Type: new Abstract: LLM-based foundation agents that perceive, reason, and act across thousands of reasoning steps are rapidly becoming the dominant paradigm for deploying

agentsarxiv-cs-ai

Tools

Automate progressive rollouts with Vercel Flags

Vercel Flags enables automated progressive rollouts, allowing developers to gradually deploy features to increasing percentages of users rather than releasing to everyone simultaneously. This approach

toolsvercel-blog

Cloud Storage Rapid: Turbocharged object storage for AI and analytics

model-releasesgoogle-cloud-ai

At Google Cloud Next ’26 we announced Cloud Storage Rapid, a family of object storage capabilities for data-intensive workloads like AI and analytics. Out of the gate, Cloud Storage Rapid consists of

Cluster-level reliability for trillion-parameter models on TPUs

model-releasesgoogle-cloud-ai

Frontier AI models have redefined the unit of compute. At trillion-parameter scale, AI training requires thousands of interconnected components, orchestrated in industrial-scale deployments to operate

Code Generation and Conic Constraints for Model-Predictive Control on Microcontrollers with Conic-TinyMPC

arXiv:2403.18149v3 Announce Type: replace Abstract: Model-predictive control (MPC) is a state-of-the-art control method for constrained robotic systems, yet deployment on resource-limited hardware rem

researcharxiv-cs-ro

Hardware

DeepFedNAS: Efficient Hardware-Aware Architecture Adaptation for Heterogeneous IoT Federations via Pareto-Guided Supernet Training

arXiv:2601.15127v3 Announce Type: replace-cross Abstract: Deploying federated learning across heterogeneous IoT device fleets requires tailored neural network architectures for each device class, yet

hardwarearxiv-cs-cv

OpenAI launches DeployCo to help businesses build around intelligence

OpenAI launched DeployCo, a new service designed to assist businesses in building and deploying applications leveraging OpenAI's AI models and intelligence capabilities. The offering appears to focus

model-releasesopenai

the best teams building agents ship early and iterate quickly you can't just ship an agent and then forget about the key to getting the best…

Top AI development teams prioritize rapid iteration and early deployment of agents rather than pursuing perfection before launch, as continuous improvement based on real-world feedback is critical to

agentsharrison-chase--x

9 May 2026

A Regulatory Governance Framework for AI-Driven Financial Fraud Detection in U.S. Banking: Integrating OCC, SR 11-7, CFPB, and FinCEN Compliance Requirements for Model Development, Validation, and Monitoring Lifecycles

model-releasesarxiv-cs-lg

arXiv:2605.04076v1 Announce Type: new Abstract: U.S. financial institutions deploying AI-based fraud detection face a fragmented compliance landscape spanning four regulatory frameworks -- OCC Bulleti

Adaptive Policy Selection and Fine-Tuning under Interaction Budgets for Offline-to-Online Reinforcement Learning

arXiv:2605.05123v1 Announce Type: new Abstract: In offline-to-online reinforcement learning (O2O-RL), policies are first safely trained offline using previously collected datasets and then further fin

AI agents on Ray Serve: Single to multi-agent architecture

This guide explores deploying AI agents using Ray Serve, covering architectural patterns that scale from single-agent to multi-agent systems. It likely demonstrates how to structure agent applications

agentsanyscale-ray

Local Ai

Available now on local and 1-2 hours on cloud 🫡

ComfyUI announced the availability of a feature or service that can be accessed locally immediately and on cloud infrastructure with a 1-2 hour latency or deployment time. This post likely refers to a

local-aicomfyui--x

Constraint-Enhanced Reinforcement Learning Based on Dynamic Decoupled Spherical Radial Squashing

model-releasesarxiv-cs-lg

arXiv:2605.04185v1 Announce Type: new Abstract: When deploying reinforcement learning policies to physical robots, actuator rate constraints -- hard limits on how fast each joint can move per control

Local Ai

Hardware-Aware Neural Feature Extraction for Resource-Constrained Devices

arXiv:2605.04282v1 Announce Type: new Abstract: Visual SLAM is a core component of spatial computing systems, yet deploying learned local feature extractors on microcontroller-class hardware remains c

local-aiarxiv-cs-lg

Labs; “we will have a nation of geniuses in a data center by 2028, capable of beating humans at every task, but you will need to hire our ne…

applicationsethan-mollick--x

Labs; “we will have a nation of geniuses in a data center by 2028, capable of beating humans at every task, but you will need to hire our newly trained forward-deployed engineers for a six month engag

Syntax- and Compilation-Preserving Evasion of LLM Vulnerability Detectors

model-releasesarxiv-cs-lg

arXiv:2602.00305v2 Announce Type: replace-cross Abstract: LLM-based vulnerability detectors are increasingly deployed in CI/CD security gating, yet their resilience to evasion under syntax- and compil

Using Common Random Numbers for Simulation-based Planning with Rollouts

arXiv:2605.04732v1 Announce Type: new Abstract: Simulation-based planning with rollouts is a widely-deployed technique for decision making in stochastic environments. The primary instrument of simulat

AI Safety as Control of Irreversibility: A Systems Framework for Decision-Energy and Sovereignty Boundaries

model-releasesarxiv-cs-ai

arXiv:2605.01415v1 Announce Type: new Abstract: Recent AI systems compress the distance between capability growth and capability deployment. Earlier high-risk technologies were slowed by capital inten

Claw-Eval: Towards Trustworthy Evaluation of Autonomous Agents

arXiv:2604.06132v2 Announce Type: replace Abstract: Large language models are increasingly deployed as autonomous agents for multi-step workflows in real-world software environments. However, existing

safetyarxiv-cs-ai

MAGE: Safeguarding LLM Agents against Long-Horizon Threats via Shadow Memory

arXiv:2605.03228v1 Announce Type: cross Abstract: As large language model (LLM)-powered agents are increasingly deployed to perform complex, real-world tasks, they face a growing class of attacks that

safetyarxiv-cs-cl

On the Privacy of LLMs: An Ablation Study

arXiv:2605.02255v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in interactive and retrieval-augmented settings, raising significant privacy concerns. While at

researcharxiv-cs-ai

Online Conformal Abstention for Factuality Control Under Adversarial Bandit Feedback

arXiv:2506.14067v4 Announce Type: replace Abstract: As interactive generative systems are increasingly deployed in real-world applications, their tendency to generate unreliable or false responses rai

applicationsarxiv-cs-lg

Position: Safety and Fairness in Agentic AI Depend on Interaction Topology, Not on Model Scale or Alignment

arXiv:2605.01147v1 Announce Type: new Abstract: As large language models are increasingly deployed as interacting agents in high-stakes decisions, the AI safety community assumes that safety propertie

safetyarxiv-cs-ai

Re-Key-Free, Risky-Free: Adaptable Model Usage Control

arXiv:2511.18772v2 Announce Type: replace-cross Abstract: Deep neural networks (DNNs) have become valuable intellectual property of model owners, due to the substantial resources required for their de

applicationsarxiv-cs-ai

Real Image Denoising with Knowledge Distillation for High-Performance Mobile NPUs

arXiv:2605.03680v1 Announce Type: new Abstract: While deep-learning-based image restoration has achieved unprecedented fidelity, deployment on mobile Neural Processing Units (NPUs) remains bottlenecke

Local Ai

RPBA-Net: An Interpretable Residual Pyramid Bilateral Affine Network for RAW-Domain ISP Enhancement

arXiv:2605.03626v1 Announce Type: new Abstract: To address module fragmentation, uninterpretable mappings, and deployment constraints in RAW-domain demosaicing, color correction, and detail enhancemen

local-aiarxiv-cs-cv

Agent Factory Recap: How Gemma 4 Taught Itself Physics

model-releasesgoogle-cloud-ai

In this episode of The Agent Factory, Vlad Kolesnikov and I sat down with Omar Sanseviero from the Developer Experience team at Google DeepMind. We explored the groundbreaking release of Gemma 4: a ne

Hardware

AgriKD: Cross-Architecture Knowledge Distillation for Efficient Leaf Disease Classification

arXiv:2605.01355v1 Announce Type: new Abstract: Automated leaf disease classification is critical for early disease detection in resource-constrained field environments. Vision Transformers (ViTs) pro

hardwarearxiv-cs-cv

CGM-JEPA: Learning Consistent Continuous Glucose Monitor Representations via Predictive Self-Supervised Pretraining

arXiv:2605.00933v1 Announce Type: new Abstract: Continuous Glucose Monitoring (CGM) can detect early metabolic subphenotypes (insulin resistance, IR; eta-cell dysfunction), but population-scale deploy

researcharxiv-cs-lg

Gated Relational Alignment via Confidence-based Distillation for Efficient VLMs

arXiv:2601.22709v3 Announce Type: replace Abstract: Vision-Language Models (VLMs) achieve strong multimodal performance but are costly to deploy, and post-training quantization often causes significan

Introducing Pinecone Marketplace: Getting to Production in Minutes

Pinecone Marketplace is a platform feature that enables users to quickly deploy pre-built vector database solutions and integrations to production environments. The marketplace likely provides curated

applicationspinecone

LiteVLA-H: Dual-Rate Vision-Language-Action Inference for Onboard Aerial Guidance and Semantic Perception

arXiv:2605.00884v1 Announce Type: new Abstract: Vision-language-action (VLA) models have shown strong semantic grounding and task generalization in manipulation, but aerial deployment remains difficul

Hardware

Quant VideoGen: Auto-Regressive Long Video Generation via 2-Bit KV-Cache Quantization

arXiv:2602.02958v4 Announce Type: replace Abstract: Despite rapid progress in autoregressive video diffusion, an emerging system algorithm bottleneck limits both deployability and generation capabilit

hardwarearxiv-cs-lg

Rationality Measurement and Theory for Reinforcement Learning Agents

arXiv:2602.04737v2 Announce Type: replace Abstract: This paper proposes a suite of rationality measures and associated theory for reinforcement learning agents, a property increasingly critical yet ra

VAUQ: Vision-Aware Uncertainty Quantification for LVLM Self-Evaluation

arXiv:2602.21054v2 Announce Type: replace-cross Abstract: Large Vision-Language Models (LVLMs) frequently hallucinate, limiting their safe deployment in real-world applications. Existing LLM self-eval

applicationsarxiv-cs-cl

Bring Your Own Prompts: Use-Case-Specific Bias and Fairness Evaluation for LLMs

model-releasesarxiv-cs-cl

arXiv:2407.10853v5 Announce Type: replace Abstract: Bias and fairness risks in Large Language Models (LLMs) vary substantially across deployment contexts, yet existing approaches lack systematic guida

How General Intelligence used agents to build an agent platform on Vercel

General Intelligence built their agent platform using AI agents themselves, leveraging Vercel's infrastructure and deployment capabilities. The approach demonstrates how autonomous agents can be used

agentsvercel-blog

Knowing When to Defer: Selective Prediction for Responsible Knowledge Tracing

model-releasesarxiv-cs-cl

arXiv:2509.21514v3 Announce Type: replace-cross Abstract: Research on Knowledge Tracing (KT) models traditionally focuses on improving predictive accuracy. However, responsible real-world deployment r

Language Models Struggle to Use Representations Learned In-Context

arXiv:2602.04212v2 Announce Type: replace Abstract: Though large language models (LLMs) have enabled great success across a wide variety of tasks, they still appear to fall short of one of the loftier

applicationsarxiv-cs-cl

Learning from Compressed CT: Feature Attention Style Transfer and Structured Factorized Projections for Resource-Efficient Medical Image Analysis

arXiv:2605.00448v1 Announce Type: new Abstract: The deployment of artificial intelligence in medical imaging is hindered by high computational complexity and resource-intensive processing of volumetri