Search: “deployment”

Convergent Stochastic Training of Attention and Understanding LoRA

arXiv:2605.07959v1 Announce Type: new Abstract: Transformers have revolutionized machine learning and deploying attention layers in the model is increasingly standard across a myriad of applications.

researcharxiv-cs-lg

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CSR: Infinite-Horizon Real-Time Policies with Massive Cached State Representations

DGX agent

arXiv:2605.07325v1 Announce Type: cross Abstract: Deploying massive large language models (LLMs) as continuous cognitive engines for robotics is bottlenecked by the time-to-first-token (TTFT) latency

model-releasesarxiv-cs-ai

11 May 2026

CyBiasBench: Benchmarking Bias in LLM Agents for Cyber-Attack Scenarios

arXiv:2605.07830v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as autonomous agents in offensive cybersecurity. In this paper, we reveal an interesting phenom

DRIP-R: A Benchmark for Decision-Making and Reasoning Under Real-World Policy Ambiguity in the Retail Domain

arXiv:2605.07699v1 Announce Type: cross Abstract: LLM-based agents are increasingly deployed for routine but consequential tasks in real-world domains, where their behavior is governed by inherently a

Effective and Memory-Efficient Alternatives to ECC for Reliable Large-Scale DNNs

arXiv:2605.07417v1 Announce Type: cross Abstract: Modern Deep Learning (DL) workloads are increasingly deployed in safety-critical domains, such as automotive systems and hyperscale data centers, wher

EGA: Adapting Frozen Encoders for Vector Search with Bounded Out-of-Distribution Degradation

arXiv:2605.05674v2 Announce Type: replace-cross Abstract: Vector search systems built on frozen vision encoders face queries from unseen classes at deployment, yet existing adapter training collapses

Escaping the Diversity Trap in Robotic Manipulation via Anchor-Centric Adaptation

arXiv:2605.07381v1 Announce Type: cross Abstract: While Vision-Language-Action (VLA) models offer broad general capabilities, deploying them on specific hardware requires real-world adaptation to brid

Local Ai

FLAM: Evaluating Model Performance with Aggregatable Measures in Federated Learning

arXiv:2605.07962v1 Announce Type: new Abstract: Performance evaluation is essential for assessing the quality of machine learning (ML) models and guiding deployment decisions. In federated learning (F

local-aiarxiv-cs-lg

How Far Are VLMs from Privacy Awareness in the Physical World? An Empirical Study

arXiv:2605.05340v2 Announce Type: replace-cross Abstract: As Vision-Language Models (VLMs) are increasingly deployed as autonomous cognitive cores for embodied assistants, evaluating their privacy awa

Into the Rabbit Hull: From Task-Relevant Concepts in DINO to Minkowski Geometry

arXiv:2510.08638v3 Announce Type: replace-cross Abstract: DINOv2 is routinely deployed to recognize objects, scenes, and actions; yet the nature of what it perceives remains unknown. As a working base

researcharxiv-cs-ai

LLMs are not (consistently) Bayesian: Quantifying internal (in)consistencies of LLMs' probabilistic beliefs

arXiv:2605.06915v1 Announce Type: new Abstract: Modern AI systems are being deployed in complex domains such as medicine, science, and law, where it is important that they not only produce correct ans

researcharxiv-cs-lg

MAGIQ: A Post-Quantum Multi-Agentic AI Governance System with Provable Security

arXiv:2605.06933v1 Announce Type: new Abstract: Our computing ecosystem is being transformed by two emerging paradigms: the increased deployment of agentic AI systems and advancements in quantum compu

OpenAI launches professional services business with $4B investment

model-releasessiliconangle

OpenAI Group PBC today unveiled a new business unit, The OpenAI Deployment Company, that will help companies adopt its artificial intelligence models. The subsidiary is launching with 4 billion in fun

Outlier Smoothing with Closed-Form Rotations for W4A4 Large Language Model Quantization

arXiv:2511.22316v2 Announce Type: replace Abstract: Large Language Models (LLMs) quantization facilitates deploying LLMs in resource-limited settings, but existing methods that combine incompatible gr

Query-efficient model evaluation using cached responses

arXiv:2605.07096v1 Announce Type: cross Abstract: Evaluating a new model on an existing benchmark is often necessary to understand its behavior before deployment. For modern evaluation frameworks, gen

Reason to Play: Behavioral and Brain Alignment Between Frontier LRMs and Human Game Learners

arXiv:2605.08019v1 Announce Type: new Abstract: Humans rapidly learn abstract knowledge when encountering novel environments and flexibly deploy this knowledge to guide efficient and intelligent actio

RedDiffuser: Auditing Multimodal Safety Failures in Vision-Language Models via Reinforced Diffusion

model-releasesarxiv-cs-cv

arXiv:2503.06223v5 Announce Type: replace Abstract: Large Vision-Language Models (VLMs) are increasingly deployed in open-ended environments, where ensuring reliable safety under multimodal inputs is

Robust and Reliable AI for Predictive Quality in Semiconductor Materials Manufacturing with MLOps and Uncertainty Quantification

arXiv:2605.07752v1 Announce Type: new Abstract: Semiconductor materials manufacturing presents unique challenges for machine learning deployment due to evolving process conditions, equipment degradati

applicationsarxiv-cs-lg

Saliency-Aware Regularized Quantization Calibration for Large Language Models

arXiv:2605.05693v2 Announce Type: replace Abstract: Post-training quantization (PTQ) is an effective approach for deploying large language models (LLMs) under memory and latency constraints. Most exis

researcharxiv-cs-ai

Searching for Privacy Risks in LLM Agents via Simulation

arXiv:2508.10880v3 Announce Type: replace-cross Abstract: The widespread deployment of LLM-based agents is likely to introduce a critical privacy threat: malicious agents that proactively engage other

agentsarxiv-cs-ai

SHARP: A Self-Evolving Human-Auditable Rubric Policy for Financial Trading Agents

arXiv:2605.06822v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed for autonomous financial trading, a domain requiring continuous adaptation to noisy, non-stationa

Sparse Autoencoders as Plug-and-Play Firewalls for Adversarial Attack Detection in VLMs

arXiv:2605.07447v1 Announce Type: cross Abstract: Vision-language models (VLMs) have advanced rapidly and are increasingly deployed in real-world applications, especially with the rise of agent-based

The Context Gathering Decision Process: A POMDP Framework for Agentic Search

arXiv:2605.07042v1 Announce Type: new Abstract: Large Language Model (LLM) agents are deployed in complex environments -- such as massive codebases, enterprise databases, and conversational histories

agentsarxiv-cs-ai

Why Does Agentic Safety Fail to Generalize Across Tasks?

arXiv:2605.06992v1 Announce Type: new Abstract: AI agents are increasingly deployed in multi-task settings, where the task to perform is specified at test time, and the agent must generalize to unseen

Hardware

XiYOLO: Energy-Aware Object Detection via Iterative Architecture Search and Scaling

arXiv:2605.06927v1 Announce Type: cross Abstract: Object detection on heterogeneous edge devices must satisfy strict energy, latency, and memory constraints while still providing reliable perception f

hardwarearxiv-cs-ai

Tools

How Superset built the IDE for AI agents on Vercel

Superset developed an integrated development environment (IDE) for AI agents deployed on Vercel's platform, enabling developers to build, test, and manage AI agent applications more efficiently. The s

toolsvercel-blog

10 May 2026

@NousResearch @OpenRouter Congrats! 🙌

Nous Research announced a congratulatory message regarding a collaboration or achievement involving OpenRouter, likely related to AI model deployment or integration. The post celebrates a milestone or

researchnous-research--x

9 May 2026

Kimi K2.6 on @baseten is ~5x cheaper than Opus 4.7 For a large majority of tasks, it's roughly the same performance If you want to use open …

Kimi K2.6, deployed on Baseten, offers approximately 5x cost savings compared to Claude Opus 4.7 while maintaining comparable performance on most tasks, making it a viable open-source alternative for

agentsharrison-chase--x

8 May 2026

Running Codex safely at OpenAI

This OpenAI article outlines safety practices and guidelines for responsibly deploying and using Codex, their code generation model. It likely covers potential risks associated with automated code gen

agentsopenai

8 May 2026

3.5 years into the “AI revolution” Basically no sign that it has mattered for productivity.

Gary Marcus argues that despite 3.5 years of rapid AI development and deployment, there is minimal empirical evidence that AI has significantly impacted overall economic productivity metrics. The post

safetygary-marcus--x

Local Ai

A Workflow-Oriented Framework for Asynchronous Human-AI Collaboration in Hybrid and Compute-Intensive HPC Environments

arXiv:2605.03743v1 Announce Type: cross Abstract: Human involvement is critical in training and deploying AI systems in high-stakes defence and security contexts. However, real-time interaction is imp

local-aiarxiv-cs-ai

Beyond Semantics: An Evidential Reasoning-Aware Multi-View Learning Framework for Trustworthy Mental Health Prediction

arXiv:2605.05121v1 Announce Type: new Abstract: Automated mental health prediction using textual data has shown promising results with deep learning and large language models. However, deploying these

applicationsarxiv-cs-cl

Continual Knowledge Updating in LLM Systems: Learning Through Multi-Timescale Memory Dynamics

arXiv:2605.05097v1 Announce Type: cross Abstract: LLMs are trained once, then deployed into a world that never stops changing. External memory compensates for this, but most systems manage it explicit

researcharxiv-cs-cl

CRAFT: Counterfactual-to-Interactive Reinforcement Fine-Tuning for Driving Policies

arXiv:2605.04470v1 Announce Type: new Abstract: Open-loop imitation learning has advanced modern autonomous driving policy architectures, but closed-loop deployment remains vulnerable to policy-induce

EdgeRazor: A Lightweight Framework for Large Language Models via Mixed-Precision Quantization-Aware Distillation

arXiv:2605.04062v1 Announce Type: new Abstract: Recent years have witnessed an increasing interest in deploying LLMs on resource-constrained devices, among which quantization has emerged as a promisin

researcharxiv-cs-lg

Enhancing Agent Safety Judgment: Controlled Benchmark Rewriting and Analogical Reasoning for Deceptive Out-of-Distribution Scenarios

arXiv:2605.03242v1 Announce Type: new Abstract: Tool-using agent systems powered by large language models (LLMs) are increasingly deployed across web, app, operating-system, and transactional environm

Every so often I think about how, in 2022, for $24B we could had 'prototype vaccines ready for each of the 26 known viral families that caus…

applicationsethan-mollick--x

Every so often I think about how, in 2022, for $24B we could had 'prototype vaccines ready for each of the 26 known viral families that cause human disease' so they can be deployed in 100 days if ther

Explaining and Preventing Alignment Collapse in Iterative RLHF

arXiv:2605.04266v1 Announce Type: new Abstract: Reinforcement learning from human feedback (RLHF) typically assumes a static or non-strategic reward model (RM). In iterative deployment, however, the p

FASQ: Flexible Accelerated Subspace Quantization for Calibration-Free LLM Compression

arXiv:2605.04084v1 Announce Type: new Abstract: Compressing large language models (LLMs) for deployment on commodity GPUs remains challenging: conventional scalar quantization is limited to fixed bit-

Laundering AI Authority with Adversarial Examples

arXiv:2605.04261v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly deployed as trusted authorities -- fact-checking images on social media, comparing products, and modera

LLMs Uncertainty Quantification via Adaptive Conformal Semantic Entropy

arXiv:2605.04295v1 Announce Type: new Abstract: LLMs' overconfidence, particularly when hallucinating, poses a significant challenge for the deployment of the models in safety-critical settings and ma

Order Matters: Improving Domain Adaptation by Reordering Data

arXiv:2605.05084v1 Announce Type: new Abstract: Domain shift remains a key challenge in deploying machine learning models to the real world. Unsupervised domain adaptation (UDA) aims to address this b

Local Ai

Personalized Spiking Neural Networks with Ferroelectric Synapses for EEG Signal Processing

arXiv:2601.00020v3 Announce Type: replace-cross Abstract: Electroencephalography (EEG)-based brain-computer interfaces (BCIs) are strongly affected by non-stationary neural signals that vary across se

local-aiarxiv-cs-lg

ProgramBench: Can Language Models Rebuild Programs From Scratch?

arXiv:2605.03546v1 Announce Type: cross Abstract: Turning ideas into full software projects from scratch has become a popular use case for language models. Agents are being deployed to seed, maintain,

agentsarxiv-cs-ai

Quantization and Fast Inference (MEAP) - How much performance are you actually getting from quantization in production? [D]

applicationsr-machinelearning

This discussion examines the practical performance gains of quantization techniques when deployed in production environments, particularly addressing whether theoretical speedups translate to real-wor

Variance Matters: Improving Domain Adaptation via Stratified Sampling

arXiv:2512.05226v2 Announce Type: replace Abstract: Domain shift remains a key challenge in deploying machine learning models to the real world. Unsupervised domain adaptation (UDA) aims to address th

Hardware

When Agents Handle Secrets: A Survey of Confidential Computing for Agentic AI

arXiv:2605.03213v1 Announce Type: cross Abstract: Agentic AI systems, specifically LLM-driven agents that plan, invoke tools, maintain persistent memory, and delegate tasks to peer agents via protocol

hardwarearxiv-cs-ai

AI and Open-data Driven Scalable Solar Power Profiling

arXiv:2605.02738v1 Announce Type: new Abstract: Solar photovoltaic (PV) deployment is expanding rapidly, yet detailed, up-to-date information on the spatial distribution and capacity of rooftop PV rem