Search: “deployment”

Cross-Lingual Bias in Large Language Models: A Comparative Analysis of English and Swahili

arXiv:2608.03532v1 Announce Type: new Abstract: Large language models are increasingly deployed in multilingual contexts, yet safety alignment and bias evaluation remain overwhelmingly English-centric

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Lightweight Chunk Selection for Mobile Retrieval-Augmented Generation

DGX agent

arXiv:2608.03148v1 Announce Type: cross Abstract: RAG improves the factual grounding of LLM by incorporating external knowledge, but deploying RAG on mobile and edge devices remains challenging becaus

model-releasesarxiv-cs-ai

5 Aug 2026

Measurement Without Validity: The Compounding Reliability Problem in Agentic AI Evaluation

arXiv:2608.00794v2 Announce Type: replace Abstract: Agentic AI evaluation pipelines produce benchmark scores that justify deployment decisions, safety certifications, and regulatory compliance claims.

Morphology-Aware Implicit Super-Resolution Network for Pathological Images

model-releasesarxiv-cs-cv

arXiv:2608.03664v1 Announce Type: new Abstract: Accurate diagnosis in Digital Pathology (DP) relies on high-resolution whole-slide images, yet clinical deployment is often limited by hardware costs. S

Tutorials

Population-Robust Feature Selection via Generalized Welfare Optimization

arXiv:2608.02887v1 Announce Type: new Abstract: Choosing which features to collect is a deployment decision: the same limited questionnaire, test panel, or sensor set may need to serve several heterog

tutorialsarxiv-cs-lg

ZK-SR117: A Chunked Zero-Knowledge Attestation Design for Aggregated Fair-Lending Metrics, with a Control Mapping toward Full SR 11-7 Coverage

arXiv:2608.02664v1 Announce Type: cross Abstract: Deploying ML models in regulated decision-making (credit underwriting, fraud detection, loan approval) requires demonstrating fairness and robustness

Domain-Generalized Adaptive Semantic Communication for Collaborative Perception

arXiv:2608.00056v1 Announce Type: cross Abstract: We propose RSTA, a domain-generalized semantic communication framework enabling source-free V2X collaborative perception under both observation-domain

safetyarxiv-cs-lg

Grounding Agentic VLMs with Dedicated Segmentation for Fine-Grained Vehicle Damage Assessment

model-releasesarxiv-cs-cv

arXiv:2608.02470v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly deployed as reasoning agents in real-world visual assessment pipelines, yet their spatial grounding remai

Hardware

HetRoute Heterogeneous and Cost-aware Collaborative Routing Framework for Distributed Edge MoE Inference

arXiv:2608.00577v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models have become a dominant architecture for large-scale AI services, yet deploying them over geo-distributed heterogeneous

hardwarearxiv-cs-cl

Latency-Tolerant Cloud-Edge Collaborative Vision-Language-Action Models via Emergent Representational Specialization

model-releasesarxiv-cs-ro

arXiv:2608.00569v1 Announce Type: new Abstract: Deploying billion-parameter Vision-Language-Action (VLA) policies on mobile robots creates a systems conflict: semantic reasoning benefits from cloud GP

Meganeura: Portable GPU Training and Inference through Vulkan and Metal

arXiv:2608.01563v1 Announce Type: new Abstract: Training and deployed inference often cross export, conversion, and platform-specific runtime boundaries. Meganeura asks whether one compact native comp

safetyarxiv-cs-lg

PredAct-Bench: Benchmarking Tool-Augmented Dialogue under Controlled Tool Noise

arXiv:2608.02372v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in task-oriented dialogue systems that support multi-step decision-making in high-stakes domains

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models

model-releasesarxiv-cs-lg

arXiv:2506.07121v2 Announce Type: replace Abstract: Ensuring the safety and robustness of large language models (LLMs) is a fundamental challenge and a critical prerequisite for the responsible deploy

Training-Free Out-of-Distribution Detection for Pathology Whole-Slide Images

arXiv:2608.01407v1 Announce Type: new Abstract: Safe deployment of AI methods in medicine requires robust guardrails that detect when input data deviate from the training distribution to ensure that m

researcharxiv-cs-cv

Understanding Sparse Attention Selectivity in Long-Context Foundation Models via Counterfactual Evaluation

arXiv:2608.01676v1 Announce Type: new Abstract: Sparse attention is widely deployed in long-context serving stacks, yet no framework audits how discarding blocks changes the influence of specific cont

researcharxiv-cs-cl

Local Ai

VespaSeg: A Resource-Aware Ground-then-Segment Pipeline for Referring Expression Segmentation

arXiv:2608.01077v1 Announce Type: new Abstract: Referring expression segmentation requires language conditioned localization and pixel-accurate masks, but monolithic models can be costly to deploy. We

local-aiarxiv-cs-ro

Bootstrapping Self-Supervised Learning of Binary Classification Using Error Bounds: A Case Study on a Robotic Insertion Task

model-releasesarxiv-cs-ro

arXiv:2607.29640v1 Announce Type: new Abstract: Flexible manufacturing requires rapid deployment of solutions and minimal setup time to remain competitive. An essential attribute is the ability to con

CLIFT: Turning Gemini Robotics On-Device into Humanoid Specialists via Non-Invasive Closed-Loop Iterative Fine-Tuning

arXiv:2607.29172v1 Announce Type: cross Abstract: While robot foundation models are growing increasingly capable, the strongest models are typically trained on proprietary data and remain closed-sourc

Local Ai

GQ-FSL: Green Quantized Federated Split Learning

arXiv:2607.29659v1 Announce Type: new Abstract: Deploying state-of-the-art deep neural networks (DNNs) at the wireless edge is severely bottlenecked by the strict energy and resource constraints of mo

local-aiarxiv-cs-lg

MAGA: Multi-Platform Self-Fusion of GUI Agents via Structured Action Distillation

arXiv:2607.29320v1 Announce Type: new Abstract: Graphical user interface (GUI) agents based on large language models are increasingly deployed across mobile, web, and desktop environments. However, ex

When Unlearning Fails: Reliable Data Deletion under Post-Training in Agent Networks

arXiv:2607.28829v1 Announce Type: cross Abstract: Self-improving federated agent networks keep training after deployment by collecting new trajectories with the current policy and feeding them back in

safetyarxiv-cs-lg

IFHierBench: Hierarchical Instruction Following for Large Language Models

arXiv:2607.27912v1 Announce Type: cross Abstract: Instruction-following ability is critical for deploying large language models in real-world applications, where downstream components depend on the ou

RoboBRIDGE: A Modular Framework for Bridging Policies to Robust Real-World Robotic Agents

arXiv:2607.27881v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have attracted growing interest as a scalable approach to robotic manipulation. While these models are effective act

agentsarxiv-cs-ro

Selecting Open-Weight Language Models for Zero-Shot Intent Classification: A Systematic Evaluation of 41 Models

arXiv:2607.27421v1 Announce Type: new Abstract: Intent classification is a core component of task-oriented dialogue systems, yet practitioners have limited systematic guidance for selecting deployable

ServerlessT2I: Efficient Text-to-Image Workflow Serving on a Serverless Platform

arXiv:2607.26566v1 Announce Type: cross Abstract: Text-to-image (T2I) workflows are increasingly deployed on serverless platforms because users often compose customized workflows and invoke them inter

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation

arXiv:2607.27890v1 Announce Type: new Abstract: Visuomotor policies have advanced on manipulation tasks where the target object stays static during execution, but real deployments break this assumptio

safetyarxiv-cs-ro

The Human Utility Factor: A Computable Welfare Metric That Reframes AI Governance as a Constrained Optimisation Problem

arXiv:2607.26068v1 Announce Type: cross Abstract: Existing AI governance frameworks, including the EU AI Act and NIST AI RMF, address safety, transparency, and accountability but do not operationalize

Choosing Where and How to Moderate: End-to-End Trade-offs in Filter Placement and Response Rewriting

arXiv:2607.26200v1 Announce Type: new Abstract: Content-moderation classifiers are usually evaluated in isolation, but deployment requires choosing where to intervene and what follows a flag. We evalu

30 Jul 2026

Do more with less: How GKE can reduce your cost per agent by 75%

In today’s agentic era, modern cloud applications are evolving from a set of passive tools to fleets of autonomous digital workers that reason, plan, and take action across a wide range of tasks. For

agentsgoogle-cloud-ai

30 Jul 2026

Reinforcement Learning on Cost-Constrained Quadrupedal Hardware

arXiv:2607.26434v1 Announce Type: new Abstract: Deploying learned control policies on low-cost robotic platforms introduces transport latencies and noisy motor feedback that systematically widens the

researcharxiv-cs-ro

30 Jul 2026

Do Models Fake Alignment Without Clear Consequences?

arXiv:2607.24758v1 Announce Type: new Abstract: Large language models are capable of recognizing evaluation contexts and altering their behavior to reflect evaluator expectations rather than typical d

HANDBOOK.md: A Benchmark for Long-Context Agentic Instruction Following

arXiv:2607.25398v1 Announce Type: new Abstract: Language-model agents are increasingly deployed under standing instructions: a system prompt, a policy file, or a skills document is placed in context,

HOBA: Hierarchical On-Policy Bidding Agents for Adaptive Online Advertising

arXiv:2607.24779v1 Announce Type: new Abstract: Online advertising bidding systems typically deploy multiple offline-trained expert models (e.g., PID controllers, model predictive control, offline RL

On the Use of Synthetic Data for Threshold Calibration in Face Recognition: Performance and Security Implications for Border Control Systems

arXiv:2607.25990v1 Announce Type: new Abstract: The recently deployed Entry/Exit System (EES) introduces large-scale biometric verification into European border control, requiring face recognition sys

safetyarxiv-cs-cv

UniMem: Complementary Episodic-to-Parametric Memory for Boundary-Agnostic Task Streams

arXiv:2607.26017v1 Announce Type: new Abstract: Memory is essential for LLM agents to accumulate task experience and reuse task-specific execution strategies. However, real-world deployment over bound

Bigger or Cheaper? Scale and Quantization Effects on Uncertainty Signals in Vision-Language Models Under Image Degradation

arXiv:2607.24440v1 Announce Type: cross Abstract: Vision-language models (VLMs) deployed on consumer hardware must decide when to answer and when to defer, and that decision depends on having a confid

researcharxiv-cs-cl

Bringing Conversational Analytics to your entire data ecosystem

model-releasesgoogle-cloud-ai

Increasing the adoption of generative AI across the enterprise requires you to do more than deploy a generic chatbot with a custom wrapper. Interacting with business-critical databases demands absolut

ESF-Bench: Benchmarking Challenging Slot-Filling Scenarios for Real-World Enterprise Applications

arXiv:2607.23326v1 Announce Type: new Abstract: The rapid rise of large language models (LLMs) has driven transformative adoption across enterprises. However, deploying these models in real-world sett

From Data to Device: ELMOD An Efficient German-First 2.7B Language Model for Mobile Inference

arXiv:2607.24585v1 Announce Type: new Abstract: We present ELMOD - Efficient Language Model for On-Device Deployment - a compact (2.7B) German language model designed for efficient inference on resour

Lexical discovery in unknown environments orchestrated by Large Language Models

arXiv:2607.22591v1 Announce Type: new Abstract: Populations of autonomous agents deployed in unknown environments (e.g. planetary or deep-sea exploration) must develop shared vocabularies to refer to

agentsarxiv-cs-ai

MMOE: Modernizing Diffusion Transformers with Efficient Expert Design

model-releasesarxiv-cs-cv

arXiv:2607.24665v1 Announce Type: new Abstract: Modern large language models scale successfully by pairing capacity growth with efficiency, keeping per-token and deployment costs under control as capa

PANOPTICON: A PII-Based Assemblage of Naturalistic Output Tokens for Investigating Privacy Leakage Within LLM Context Window

arXiv:2607.22695v1 Announce Type: new Abstract: Large Language Models (LLMs) are capable of generalizing human language for the completion of never-before-seen tasks, leading to widespread deployment.

Same Predictions, Different Reasons: The Effect of Quantization on Model Explanations

arXiv:2607.22872v1 Announce Type: cross Abstract: Post-training quantization (PTQ) has become a practical solution for deploying deep learning models on resource-constrained edge devices by compressin

researcharxiv-cs-cv

Local Ai

SLA-Constrained Carbon-Aware Routing in Geo-Distributed Serverless Clouds

arXiv:2607.22806v1 Announce Type: new Abstract: Modern cloud deployments distribute applications across multiple geographic regions, yet standard routing mechanisms prioritize latency while ignoring t

local-aiarxiv-cs-lg

SpecBox: Speculative Sandbox Scheduling for Efficient LLM Agent Serving

arXiv:2607.23933v1 Announce Type: cross Abstract: As LLM agents increasingly rely on the Model Context Protocol (MCP) to invoke isolated external sandboxes, disaggregated sandbox deployment introduces

agentsarxiv-cs-ai

TRIDENT: Benchmarking LLM Safety in Finance, Medicine, and Law

arXiv:2507.21134v2 Announce Type: replace Abstract: As large language models (LLMs) are increasingly deployed in high-risk domains such as law, finance, and medicine, systematically evaluating their d

Automatic Map Density Selection for Locally-Performant Visual Place Recognition

arXiv:2602.21473v3 Announce Type: replace Abstract: A key challenge in translating Visual Place Recognition (VPR) from the lab to long-term deployment is ensuring a priori that a system can meet user-

researcharxiv-cs-cv

27 Jul 2026

CommandLM: Data driven behavior level descriptor for ego vehicles