Search: “deployment”

Quantization-Aware Healing: A Practical Recipe for Recovering Compressed, 4-Bit LLMs

arXiv:2608.20953v1 Announce Type: cross Abstract: Serving large language models cheaply increasingly means shipping models that are both structurally compressed to a fraction of their parameters and q

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Safety

Robust Validation to Geometric Perturbations for Autonomous Pose Estimation

DGX agent

arXiv:2608.21066v1 Announce Type: new Abstract: Deploying autonomous systems in safety-critical domains demands guaranteed robustness against physically plausible geometric perturbations rather than a

safetyarxiv-cs-cv

24 Aug 2026

Self-Speculation for Faster Reasoning Models

arXiv:2608.20359v1 Announce Type: new Abstract: Large language models (LLMs) are deployed for increasingly complex tasks involving planning and multi-step decision making, but high-quality performance

SPARC: Single-Pass Scaling for Motion Forecasting with Conformal Bayesian Last Layers

arXiv:2608.20802v1 Announce Type: new Abstract: Human motion forecasters are increasingly accurate and fast, but reliable deployment requires uncertainty estimates that are structured, calibrated, and

researcharxiv-cs-ai

Structure for Reading, Prose for Writing: Asymmetric Structural Conditioning in Multi-Agent Document Authoring

arXiv:2608.20786v1 Announce Type: new Abstract: Multi-agent pipelines that author formal documents must both read a requester's forms and write against them. We report a deployed tender-response syste

Local Ai

Thermo-FL: Thermal-Aware Robust Federated Fine-Tuning of Large Language Models for Edge AI

arXiv:2608.21172v1 Announce Type: new Abstract: Federated fine-tuning enables large language models to adapt on edge devices without centralizing private data, but practical deployments must address h

local-aiarxiv-cs-lg

Towards Traffic Modelling of Multi-Agent Systems: The Role of Coordination Topology

arXiv:2608.20494v1 Announce Type: cross Abstract: Multi-agent LLM systems are an emerging networked workload whose rapid deployment raises questions about the traffic patterns they generate. Compared

An Irreducible Quantum Advantage in Aligning World Models with Reality

arXiv:2608.19779v1 Announce Type: cross Abstract: World models provide digital simulacra of the true world, allowing agents to be trained and tested before costly real-world deployment. At each time s

Can Agent Memory Systems Track Evolving State?

arXiv:2608.19652v1 Announce Type: new Abstract: As LLM-based agents are deployed for longer and higher-stakes tasks, their memory systems continue to have crucial gaps. While existing memory benchmark

Cloud CISO Perspectives: Sticking to security fundamentals in the AI era

model-releasesgoogle-cloud-ai

Welcome to the first Cloud CISO Perspectives for August 2026. Today, Chris Betz explains why the AI era makes it more important than ever to lean into security fundamentals.As with all Cloud CISO Pers

Compliance, Capability, and Conflict: Benchmarking Multimodal LLMs under System Messages

arXiv:2608.19207v1 Announce Type: new Abstract: Production deployments of Multimodal Large Language Models (MLLMs) increasingly rely on system messages to govern model behavior. Yet existing benchmark

DiverValue-Bench: A Benchmark and Fine-Tuning Framework for Aligning Large Language Models with Diverse Human Values

arXiv:2509.08022v3 Announce Type: replace-cross Abstract: Aligning large language models (LLMs) with diverse human values is essential for safe and effective deployment, yet existing benchmarks often

Drift-Adaptive ICU Intervention Prediction: Freezing the Physiological Encoder for Auditable Model Updating

arXiv:2607.19020v2 Announce Type: replace-cross Abstract: Clinical decision support degrades as treatment protocols evolve, but the obstacle to updating a deployed model is governance as much as accur

Enforcing LLM Safety through DMD-based Classification of Prompt-Response Embedding Dynamics

arXiv:2608.19579v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in high-stakes applications, yet their tendency to generate toxic, harmful, or policy-violating c

On the Applicability of Safety Nets: A Safety-By-Design Solution for Certifying Neural Networks

arXiv:2608.20053v1 Announce Type: new Abstract: The integration of Artificial Intelligence (AI) in safety-critical aviation systems presents significant challenges for certification and deployment. Av

Symposium: Trust via Auditable Records for Communities of AI Scientist Agents

arXiv:2608.19511v1 Announce Type: new Abstract: Symposium is a formal framework and practical implementation to record the operation of AI agents deployed by small scientific research communities. Sym

When to Retrain: An Empirical Study of Retraining Policies for Streaming ML Under Concept Drift, Budget, and Latency Constraints

arXiv:2608.19488v1 Announce Type: new Abstract: Production machine learning systems degrade under concept drift, yet practitioners have little principled guidance on when to retrain. Retraining is cos

safetyarxiv-cs-lg

10 questions every startup should answer before moving to production with their AI prototype

model-releasesgoogle-cloud-ai

It’s never been easier to start an AI-powered startup on Google Cloud. You grab an API key from Google AI Studio at breakfast, paste it into Antigravity, and by lunch you’ll have a nascent prototype o

Bridging Search and CRM: Productionizing AI Product Research Agents for Customer Re-Engagement

arXiv:2608.18543v1 Announce Type: new Abstract: Modern e-commerce platforms often operate search, recommendation, personalization, and CRM systems independently, limiting opportunities for proactive c

Detecting Backdoors in Object Detection via Pre-NMS Prediction Distribution Shift

arXiv:2608.19088v1 Announce Type: cross Abstract: Object detection models deployed in safety-critical applications remain vulnerable to backdoor attacks that cause targeted misbehaviors when a hidden

Expanding Google Antigravity for enterprise customers

model-releasesgoogle-cloud-ai

Since announcing Google Antigravity in Gemini Enterprise Agent Platform at I/O in May, we’ve heard helpful feedback from our customers. Your developers want easy access to coding agents across surface

extsc{TestifAI}: Tomography-Based Testing for Deep Learning Systems

arXiv:2608.18900v1 Announce Type: new Abstract: As AI systems are increasingly deployed in safety-critical application domains (e.g., autonomous driving), associated risks increase too. Deep learning

FedCoRe: Target-Adaptive Completion for Missing Modalities in Healthcare Federated Learning

arXiv:2608.18311v1 Announce Type: cross Abstract: Federated multimodal models often assume every site has every modality, although hospitals differ in access to EHRs, chest radiographs, and ECGs. We s

applicationsarxiv-cs-ai

LACONIC: Dense-Level Effectiveness for Scalable Sparse Retrieval via a Two-Phase Training Curriculum

arXiv:2601.01684v2 Announce Type: replace-cross Abstract: While dense retrieval models have been the standard for state-of-the-art information retrieval, their deployment is often constrained by high

Seasonal false alarms in customer churn and decline early-warning systems: adjacent-window labels confound seasonality with decline, and a year-over-year correction

arXiv:2608.18174v1 Announce Type: cross Abstract: Customer decline early-warning systems feed account-manager action lists, and every flagged account consumes intervention capacity. In a deployed busi

applicationsarxiv-cs-lg

Simple, Safe, and Overlooked: Reclaiming Sustainable Domain Generalization with Statistical Color Matching

arXiv:2608.18915v1 Announce Type: new Abstract: Hardware shifts, color variations, and changing patient characteristics between development and deployment routinely break trained medical image classif

safetyarxiv-cs-cv

SPARC: Slice-to-volume Pipeline for Automated Reconstruction of gated 3D+time fetal Cardiac MRI

arXiv:2608.18616v1 Announce Type: new Abstract: Fetal cardiac MRI (fCMR) provides valuable diagnostic information complementary to echocardiography, particularly for complex congenital heart disease (

researcharxiv-cs-cv

AI, Brain Death Detection, and Islamic Law

arXiv:2608.16903v1 Announce Type: cross Abstract: The deployment of machine learning systems capable of detecting covert consciousness in neurologically injured patients creates a profound challenge a

applicationsarxiv-cs-ai

Audio Physical Dynamics Inspired Deepfake Detection for Voice Authentication Systems

arXiv:2512.06040v2 Announce Type: replace-cross Abstract: Voice authentication systems deployed at the network edge face dual threats: a) sophisticated deepfake synthesis attacks and b) control-plane

researcharxiv-cs-ai

Benchmarking the Benchmarks: Evaluating Automated Safety Benchmarks for Small Language Models

arXiv:2608.17183v1 Announce Type: new Abstract: Small Language Models (SLMs) are increasingly deployed in resource-constrained, privacy-sensitive settings, where safety and bias failures can cause sec

Certified but Private: Scalable Zero-Knowledge Proofs for Neural Network Guarantees

arXiv:2608.17070v1 Announce Type: new Abstract: With the growing deployment of machine learning models, formal guarantees of the robustness and fairness of these models have become increasingly import

safetyarxiv-cs-lg

Delta2Gamma: Band-Wise Adaptive Contrastive Learning of EEG for Alzheimer's Disease Detection

arXiv:2608.17231v1 Announce Type: cross Abstract: Low-cost, scalable screening for dementia remains an open problem. Imaging-based diagnosis is costly and hard to deploy widely. Electroencephalography

applicationsarxiv-cs-ai

Denoised Variance-Based Pruning with Optimal Brain Bias Compensation

arXiv:2608.17657v1 Announce Type: new Abstract: Vision Transformers (ViTs) achieve state-of-the-art performance but carry massive computational overhead that restricts edge deployment. Although struct

safetyarxiv-cs-cv

Local Ai

DOW-KE: Anchor-Free Multi-Layer Knowledge Editing via Direct End-to-End Weight Optimization

arXiv:2608.16932v1 Announce Type: new Abstract: Multi-layer locate-then-edit methods for knowledge editing first optimize target residual-stream activations (anchors) at selected layers, then realize

local-aiarxiv-cs-lg

Dynamic Entanglement-Weighted Pruning for Quantum Federated Unlearning in Supply-Chain Risk Prediction

model-releasesarxiv-cs-lg

arXiv:2608.17069v1 Announce Type: cross Abstract: Federated deployments of variational quantum classifiers are attractive for cross-organisation risk prediction in supply chains, because raw data neve

Embodied-Navigator: Point, Think, Memorize, and Align for Efficient Navigation

arXiv:2608.17512v1 Announce Type: new Abstract: Although Large Vision-Language Models (VLMs) have significantly advanced embodied navigation, their direct deployment remains challenging, as existing m

safetyarxiv-cs-ro

JUMP: Single-Pass Membership Inference on Fine-Tuned Diffusion Language Models

arXiv:2607.16207v2 Announce Type: replace Abstract: Public open-weight language models are often fine-tuned on private or domain-specific data before deployment, creating a need to audit whether indiv

researcharxiv-cs-ai

MobileWorldSafety: Benchmarking GUI Agent Safety Against Environmental Injection Attacks in Android Apps

arXiv:2608.17659v1 Announce Type: cross Abstract: LLM-powered GUI agents that autonomously operate smartphones are rapidly transitioning from research prototypes to early real-world deployment. Howeve

One Pipeline, Many Transformers: Pattern-Specific Imputation Specialists for Tabular Missing Data

model-releasesarxiv-cs-lg

arXiv:2510.02625v5 Announce Type: replace Abstract: Missing data in tabular datasets forces practitioners into a hard choice: deploy a general-purpose imputer that may perform poorly for the problem a

PrivAct: Internalizing Contextual Privacy Preservation via Multi-Agent Preference Training

arXiv:2602.13840v2 Announce Type: replace Abstract: Large language model (LLM) agents are increasingly deployed in personalized tasks involving sensitive, context-dependent information, where privacy

agentsarxiv-cs-cl

Tools

Quoting Jeremy Morrell

My hypothesis is that there is a new opportunity for Extensible Software on the web. LLMs radically lower the cost of authoring extensions, and modern sandbox primitives lower the deployment cost and

toolssimon-willison

When Agents Act on Web3: An Attack-Surface Survey of MCP, Skills, and Tool Calling

arXiv:2608.17275v1 Announce Type: cross Abstract: AI agents increasingly act rather than merely read: across the Model Context Protocol (MCP) ecosystem, the share of deployed tools that modify externa

Wuying-Browser-Agent: Real-World Centric Fundamental Long-Horizon Browser Agents

arXiv:2608.17319v1 Announce Type: new Abstract: Browser agents perform well on short, clean demonstrations, but real deployment is fundamentally different: agents must sustain dozens of decisions on l

A Responsible Artificial Intelligence Framework for Groundwater Modeling

arXiv:2608.15657v1 Announce Type: new Abstract: The rapid development and widespread application of artificial intelligence (AI) have sparked intense discussions on how to deploy responsible AI system

BabelSteering: Multilingual Safety Alignment via English Steering Vectors

arXiv:2608.16577v1 Announce Type: new Abstract: Large language models (LLMs) are deployed globally in high-stakes settings, yet most safety research and alignment efforts remain concentrated on Englis

Beyond Boundary Noise: Aggregated Aleatoric Uncertainty Fails to Capture Presence Ambiguity in 3D Lung Nodule Segmentation

arXiv:2608.14766v1 Announce Type: new Abstract: Uncertainty estimation is critical for the safe clinical deployment of deep learning in medical image segmentation, with aleatoric uncertainty theoretic

safetyarxiv-cs-cv

Beyond Clear Skies: Synthetic Seasonal and Weather Variations for Real-World Drone Detection

model-releasesarxiv-cs-cv

arXiv:2608.16191v1 Announce Type: new Abstract: Reliable drone detection under real-world deployment conditions requires training data that spans the full operational design domain, including adverse

Beyond Thresholds: A Quality-Aware Decision Intelligence Framework for Cold Chain IoT Systems

arXiv:2608.15082v1 Announce Type: new Abstract: Cold chain logistics has advanced technologically, yet most deployed systems remain reactive monitors, not decision-making agents: thresholds trigger al