Knowledge catalogue
arXiv:2506.02671v3 Announce Type: replace Abstract: Deep neural networks often suffer performance degradation upon deployment due to distribution shifts. Continual Test-Time Adaptation (CTTA) aims to
arXiv:2604.27292v1 Announce Type: new Abstract: Every system that performs effects has two boundaries: what it can do (expressiveness) and what governance covers (governance). In nearly all deployed A
AI-led process modernization is redefining how enterprises deploy AI — moving beyond broad rollouts to embedding intelligence into specific, governed business processes that actually scale. But the li
arXiv:2604.25965v1 Announce Type: cross Abstract: Deep learning models are widely deployed in safety-critical domains, but remain vulnerable to adversarial attacks. In this paper, we study the adversa
arXiv:2604.26241v1 Announce Type: new Abstract: Passive RFID tags offer a cost-effective and scalable solution for tracking numerous deployed assets. However, in forested environments, signal attenuat
arXiv:2604.26557v1 Announce Type: cross Abstract: The increasing deployment of Large Language Model (LLM) inference on edge AI systems demands efficient execution under tight memory budgets. A key cha
Every year for AI Ascent, @gradypb, @Konstantine and I get to share some perspectives on AI and where things are headed. This year's talk was about the arrival of agents and the race to deploy them ac
arXiv:2604.26752v1 Announce Type: new Abstract: We present GLM-5V-Turbo, a step toward native foundation models for multimodal agents. As foundation models are increasingly deployed in real environmen
Major League Baseball opened the 2026 season with a technological first: the Automated Ball-Strike or ABS Challenge System, powered by T-Mobile’s private 5G network, is now deployed across all 29 U.S.
arXiv:2604.26569v1 Announce Type: new Abstract: Deploying a neuro-symbolic task planner on a new domain today requires significant manual effort: a domain expert must author relaxation and complementa
arXiv:2604.26516v1 Announce Type: cross Abstract: Offline reinforcement learning (RL) agents often fail when deployed, as the gap between training datasets and real environments leads to unsafe behavi
Enterprise customer experience platform provider Netomi Inc. today announced it has raised 110 million in new funding to expand its agentic artificial intelligence platform and accelerate deployment a
arXiv:2604.26091v1 Announce Type: new Abstract: We study reliability in autonomous language-model agents that translate user mandates into validated tool actions under real capital. The setting is DX
arXiv:2604.25602v2 Announce Type: replace Abstract: Deploying production-ready multi-agent systems (MAS) in complex industrial environments remains challenging due to limitations in scalability, obser
arXiv:2509.23410v4 Announce Type: replace-cross Abstract: Large language models (LLMs) deliver impressive performance but incur prohibitive memory and compute costs at deployment. Model pruning is an
arXiv:2604.26593v1 Announce Type: new Abstract: Digital twins provide a powerful paradigm for diagnostic and prognostic tasks in the monitoring and control of engineered systems; however, their deploy
arXiv:2604.26940v1 Announce Type: new Abstract: Small language models (SLMs) offer computational efficiency for scalable deployment, yet they often fall short of the reasoning power exhibited by their
This article argues that rapid software deployment and iteration do not necessarily translate to faster organizational learning or improved decision-making in data and AI projects. It likely explores
Governments worldwide are racing to show progress on AI, but the gap between declaring sovereign AI ambitions and actually deploying systems that mission operators will trust is widening fast. No plac
The TensorRT for RTX plugin provides a runtime for Unreal Engine's Neural Network Engine (NNE), enabling efficient deployment of AI models directly within real-time applications. Developers can see 1.
arXiv:2604.26181v1 Announce Type: new Abstract: Multimodal deep neural networks deployed in realistic environments must contend with runtime variations: changes in modality quality, overall input comp
arXiv:2510.04214v3 Announce Type: replace Abstract: We deploy large language models (LLMs) as business development (BD) agents for persuasive price negotiation in online travel agencies (OTAs). The ag
arXiv:2604.26317v1 Announce Type: new Abstract: The vulnerabilities of deep neural networks against singularities have raised serious concerns regarding their deployment in the physical world. One of
arXiv:2505.13963v3 Announce Type: replace Abstract: Quantization methods are widely used to accelerate inference and streamline the deployment of large language models (LLMs). Although quantization's
Editor’s note: Want to keep up with the latest from Google Cloud? Check back here for a monthly recap of our latest updates, announcements, resources, events, learning opportunities, and more. We host
arXiv:2604.26174v1 Announce Type: new Abstract: Domain shift, where deviations between training and deployment data distributions degrade model performance, is a key challenge in underwater environmen
arXiv:2604.24810v1 Announce Type: new Abstract: Edge computing environments impose strict constraints on energy consumption and latency, making the deployment of deep neural networks a significant cha
This Databricks article discusses the gap between the readiness of AI agent technology and the organizational and technical architectures needed to deploy them effectively. It likely addresses infrast
arXiv:2604.24916v1 Announce Type: new Abstract: We introduce asRoBallet, to the best of our knowledge, the first successful deployment of reinforcement learning (RL) on a humanoid ballbot hardware. Hi
arXiv:2604.25203v1 Announce Type: new Abstract: Deploying guardrails for custom policies remains challenging, as generic safety models fail to capture task-specific requirements, while prompting LLMs
arXiv:2601.03266v2 Announce Type: replace Abstract: Large language models (LLMs) have rapidly advanced in clinical decision-making, yet the deployment of proprietary systems is hindered by privacy con
Companies that have achieved success with AI implementations prioritized building a robust data foundation and infrastructure before deploying AI models. Databricks emphasizes that a well-constructed
arXiv:2604.25574v1 Announce Type: new Abstract: In autonomous driving, camera-radar fusion offers complementary sensing and low deployment cost. Existing methods perform fusion through input mixing, f
arXiv:2604.25716v1 Announce Type: new Abstract: Safety mechanisms for large language models (LLMs) remain predominantly English-centric, creating systematic vulnerabilities in multilingual deployment.
DeepInfra is an inference provider integrated with Hugging Face that enables users to deploy and run machine learning models at scale. This integration allows developers to access DeepInfra's serverle
Generative models are often deployed to make decisions on behalf of users, such as vision-language models (VLMs) identifying which person in a room is a doctor to help visually impaired individuals. Y
arXiv:2604.25135v1 Announce Type: new Abstract: Large Language Models are being increasingly deployed as the decision-making core of autonomous agents capable of effecting change in external environme
Identity Orchestration Platforms Digital identity fragments across contexts, platforms, and now AI-generated personas. These platforms reconcile, manage, and even strategically deploy multiple identit
As AI transforms healthcare operations, the industry’s most consequential challenge has shifted from building models to deploying them responsibly in regulated workflows where trust, accuracy and huma
arXiv:2512.20677v4 Announce Type: replace-cross Abstract: The increasing deployment of large language models (LLMs) in safety-critical applications raises fundamental challenges in systematically eval
arXiv:2601.21293v2 Announce Type: replace Abstract: Reliability-centered prognostics for rotating machinery requires early-warning signals that remain accurate under nonstationary operating conditions
This post shows you how to deploy a serverless MCP proxy on Amazon Bedrock AgentCore Runtime that gives you a programmable layer to implement proper governance, controls, and observability aligned wit
Gary Marcus critiques the rapid deployment of chatbots to market without adequate consideration of potential harms and consequences. The statement reflects concerns about insufficient safety testing a
arXiv:2604.25359v1 Announce Type: new Abstract: Large Language Models are increasingly being deployed to extract structured data from unstructured and semi-structured sources: parsing invoices, medica
Vercel has extended Pro plan support to Stripe Projects, enabling developers using Stripe's platform to access Vercel's Pro tier features for their deployments. This integration allows Stripe customer
Dell Technologies’ AI Factory is emerging as a core building block for enterprise AI deployment, delivering full-stack infrastructure for training and inference since its 2024 launch. Yet as AI moves
arXiv:2604.23049v1 Announce Type: new Abstract: AI agents are increasingly deployed to execute tasks and make decisions within agentic workflows, introducing new requirements for safe and controlled a
arXiv:2604.23271v1 Announce Type: new Abstract: Automated white blood cell (WBC) classification is essential for scalable leukaemia screening. However, real-world deployment is challenged by domain sh
arXiv:2604.22901v1 Announce Type: new Abstract: Diffusion models achieve remarkable success in time series generation. However, slow inference limits their practical deployment. We propose E^2-CRF (Er
arXiv:2604.23483v1 Announce Type: new Abstract: Multi-component natural language processing (NLP) pipelines are increasingly deployed for high-stakes decisions, yet no existing adversarial method can
arXiv:2604.23018v1 Announce Type: cross Abstract: Web-scale 3D asset collections are abundant, but rarely deployment-ready. Assets ship with arbitrary metric scale, incorrect pivots and forward axes,
arXiv:2604.24076v1 Announce Type: new Abstract: As large language models (LLMs) are increasingly deployed in high-stakes and operational settings, evaluation strategies based solely on aggregate accur
arXiv:2604.23459v1 Announce Type: cross Abstract: Multi-agent systems (MAS), composed of networks of two or more autonomous AI agents, have become increasingly popular in production deployments, yet i
arXiv:2509.21979v4 Announce Type: replace-cross Abstract: Visual language models (VLMs) have the potential to transform medical workflows. However, the deployment is limited by sycophancy. Despite thi
arXiv:2604.23863v1 Announce Type: new Abstract: Autonomous systems are increasingly deployed in real-world environments, where they must achieve high performance while maintaining safety under state a
arXiv:2508.13650v3 Announce Type: replace Abstract: As large language models (LLMs) are increasingly deployed in real-world applications, the need to selectively remove unwanted knowledge while preser
DeepSeek V4-Pro is now available on the Fireworks AI platform, likely offering accelerated inference speeds ('Zoooooom' suggests performance optimization). This deployment enables users to access Deep
arXiv:2601.02455v2 Announce Type: replace-cross Abstract: Deploying Automatic Speech Recognition (ASR) models on memory-constrained edge devices requires aggressive low-bit weight quantization. Layer-
arXiv:2604.23801v1 Announce Type: new Abstract: Practitioners deploying small open-weight large language models (LLMs) for medical question answering face a recurring design choice: invest in a domain
arXiv:2512.03847v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) has shown strong performance in LLM post-training, but real-world deployment often involves noisy or incomplete su