Search: “deployment”

The Efficiency Frontier: A Unified Framework for Cost-Performance Optimization in LLM Context Management

arXiv:2605.23071v1 Announce Type: new Abstract: Large language models (LLMs) increasingly rely on long-context processing, but expanding context windows introduces substantial computational and financ

researcharxiv-cs-cl

25 May 2026

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Safety

Embedding-Based Federated Learning with Runtime Governance for Iron Deficiency Prediction

DGX agent

arXiv:2605.21563v1 Announce Type: new Abstract: Recent reviews find that the vast majority of published healthcare federated learning (FL) studies never reach real-world deployment. We developed an em

safetyarxiv-cs-lg

23 May 2026

Applications

Healthcare LLM Benchmarks Are Only as Good as Their Explicit Assumptions

arXiv:2605.22612v1 Announce Type: cross Abstract: Benchmarks are necessary for healthcare evaluation, but are not sufficient for predicting deployment performance. Our position is that the evaluation-

applicationsarxiv-cs-lg

23 May 2026

Distributed Multi-Coverage for Robot Swarms

arXiv:2605.21686v1 Announce Type: new Abstract: Autonomous drone swarms deployed for surveillance, environmental monitoring, and infrastructure inspection must maintain reliable coverage of critical a

agentsarxiv-cs-ro

Governance by Construction for Generalist Agents

arXiv:2605.20874v1 Announce Type: new Abstract: Enterprise agents are increasingly expected to operate autonomously across tools and interfaces, yet production deployments require governance by constr

Applications

Quantizing Whisper-small: How design choices affect ASR performance

arXiv:2511.08093v2 Announce Type: replace-cross Abstract: Large speech recognition models like Whisper-small achieve high accuracy but are difficult to deploy on edge devices due to their high computa

applicationsarxiv-cs-cl

Vendi Novelty Scores for Out-of-Distribution Detection

arXiv:2602.10062v2 Announce Type: replace-cross Abstract: Out-of-distribution (OOD) detection is critical for the safe deployment of machine learning systems. Existing post-hoc detectors typically rel

researcharxiv-cs-cv

Hardware

Accelerating Video Inverse Problem Solvers with Autoregressive Diffusion Models

arXiv:2605.20624v1 Announce Type: new Abstract: Diffusion models provide powerful priors for zero-shot video inverse problems, but their real-time deployment is hindered by two inefficiencies: high in

hardwarearxiv-cs-cv

21 May 2026

GraphRAG on Consumer Hardware: Benchmarking Local LLMs for Healthcare EHR Schema Retrieval

model-releasesarxiv-cs-cl

arXiv:2605.20815v1 Announce Type: new Abstract: Graph-based Retrieval Augmented Generation (GraphRAG) extends retrieval-augmented generation to support structured reasoning over complex corpora, but i

21 May 2026

Trusted Weights, Treacherous Optimizations? Optimization-Triggered Backdoor Attacks on LLMs

arXiv:2605.20641v1 Announce Type: cross Abstract: Inference optimization is a vital technique for deploying LLMs at scale. Compilation is the most widely adopted optimization technique for LLMs. While

21 May 2026

Adversarial Stress Testing of SPARK Humanoid Safety Filters

model-releasesarxiv-cs-ro

arXiv:2605.19009v1 Announce Type: new Abstract: Humanoid robots are difficult to deploy safely because they have high-dimensional bodies, many collision constraints, and must operate near people and o

Breaking Modality Heterogeneity in Low-Bit Quantization for Large Vision-Language Models

arXiv:2605.19929v1 Announce Type: cross Abstract: Low-bit post-training quantization (PTQ) is a pivotal technique for deploying Vision-Language Models (VLMs) on resource-constrained devices. However,

researcharxiv-cs-ai

DEFLECT: Delay-Robust Execution via Flow-matching Likelihood-Estimated Counterfactual Tuning for VLA Policies

arXiv:2605.19294v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) policies are typically deployed with asynchronous inference: the robot executes a previously predicted action chunk while

Enabling Real-Time Colonoscopic Polyp Segmentation on Commodity CPUs via Ultra-Lightweight Architecture

arXiv:2602.04381v2 Announce Type: replace-cross Abstract: Real-time polyp segmentation is essential for early colorectal cancer detection, yet clinical deployment remains blocked by GPU dependency. We

Tutorials

INAR-VL: Input-Aware Routing for Edge-Cloud Vision-Language Inference

arXiv:2605.18853v1 Announce Type: cross Abstract: Edge deployment of Vision-Language Models (VLMs) faces a tradeoff between latency and accuracy: cloud execution provides high-quality predictions but

tutorialsarxiv-cs-cv

Robotics-Inspired Guardrails for Foundation Models in Socially Sensitive Domains

arXiv:2605.19940v1 Announce Type: new Abstract: Foundation models are increasingly deployed in socially sensitive domains such as education, mental health, and caregiving, where failures are often cum

Hardware

Charon: A Unified and Fine-Grained Simulator for Large-Scale LLM Training and Inference

arXiv:2605.17164v1 Announce Type: cross Abstract: Deploying large-scale LLM training and inference with optimal performance is exceptionally challenging due to a complex design space of parallelism st

hardwarearxiv-cs-ai

Compass: SLO-aware Query Planner for Compound AI Serving at Scale

arXiv:2504.16397v2 Announce Type: replace-cross Abstract: The rise of compound AI serving that integrates multiple operators in a pipeline enables end-user applications such as generative AI-powered m

agentsarxiv-cs-lg

Compounding Disadvantage: Auditing Intersectional Bias in LLM-Generated Explanations Across Indian and American STEM Education

model-releasesarxiv-cs-cl

arXiv:2601.14506v3 Announce Type: replace-cross Abstract: Large language models are increasingly deployed in STEM education for personalized instruction and feedback across institutions in high- and l

Dance Across Shifts: Forward-Facilitation Continual Test-Time Adaptation through Dynamic Style Bridging

arXiv:2605.18608v1 Announce Type: new Abstract: Continual Test-Time Adaptation (CTTA) aims to empower perception systems to handle dynamic distribution shifts encountered after deployment. Existing me

safetyarxiv-cs-cv

Disentangling Ambiguity from Instability in Large Language Models: A Clinical Text-to-SQL Case Study

model-releasesarxiv-cs-cl

arXiv:2602.12015v2 Announce Type: replace Abstract: Deploying large language models for clinical Text-to-SQL requires distinguishing two qualitatively different causes of output diversity: (i) input a

Generating Realistic Safety-Critical Scenarios for Vehicle-Pedestrian Interactions

arXiv:2605.17229v1 Announce Type: new Abstract: Automated driving system deployment requires rigorous validation across safety-critical vehicle-pedestrian interactions, yet real-world datasets rarely

safetyarxiv-cs-ro

Generative AI Advertising as a Problem of Trustworthy Commercial Intervention

arXiv:2605.18673v1 Announce Type: cross Abstract: Major deployed generative AI advertising systems preserve a visible boundary between commercial content and AI-generated responses. Yet empirical rese

agentsarxiv-cs-cl

Goal-Conditioned Supervised Learning for LLM Fine-Tuning

arXiv:2605.16345v1 Announce Type: cross Abstract: Large language models often require fine-tuning to better align their behavior with user intent at deployment. Existing approaches are commonly divide

LivePI: More Realistic Benchmarking of Agents Against Indirect Prompt Injectio

arXiv:2605.17986v1 Announce Type: cross Abstract: AI agents such as OpenClaw are increasingly deployed in local workflows with access to external tools. This creates indirect prompt-injection (IPI) ri

LLMForge: Multi-Backend Hardware-Aware Neural Architecture Search with Infinite-Head Attention for Edge Language Models

arXiv:2605.17653v1 Announce Type: cross Abstract: Sub-billion-parameter Transformer language models are increasingly deployed on edge devices, where the privacy, latency, and operating-cost advantages

LPG: Balancing Efficiency and Policy Reasoning in Latent Policy Guardrails

arXiv:2605.17329v1 Announce Type: cross Abstract: Guardrails are a critical safety layer for modern AI systems, but their operating regime is changing. As LLMs are deployed as customized assistants, s

OSCAR: Offline Spectral Covariance-Aware Rotation for 2-bit KV Cache Quantization

arXiv:2605.17757v1 Announce Type: cross Abstract: INT2 KV-cache quantization is attractive for long-context LLM serving, but it remains difficult to make both accurate and deployable. Simple rotations

researcharxiv-cs-ai

PIMSM: Physics-Informed Multi-Scale Mamba for Stable Neural Representations under Distribution Shift

arXiv:2605.16351v1 Announce Type: cross Abstract: Scientific foundation models are expected to reuse representations under changes in dataset, acquisition protocol, and deployment domain, yet many seq

Prompt2Fingerprint: Plug-and-Play LLM Fingerprinting via Text-to-Weight Generation

arXiv:2605.18474v1 Announce Type: cross Abstract: The widespread deployment and redistribution of large language models (LLMs) have made model provenance tracking a critical challenge. While existing

Local Ai

Spiker-LL: An Energy-Efficient FPGA Accelerator Enabling Adaptive Local Learning in Spiking Neural Networks

arXiv:2605.18003v1 Announce Type: cross Abstract: Deploying adaptive intelligence at the edge remains challenging due to the high computational and energy cost of training neural models. Spiking Neura

local-aiarxiv-cs-ai

Sustainability via LLM Right-sizing

arXiv:2504.13217v3 Announce Type: replace-cross Abstract: Large language models (LLMs) have become increasingly embedded in organizational workflows. This has raised concerns over their energy consump

Transformer-Based MCS Prediction for 5G Multicast-Broadcast Services (MBS)

arXiv:2605.16735v1 Announce Type: cross Abstract: The deployment of 5G Multicast-Broadcast Services (MBS) is emerging as a critical technology for spectral-efficient UHD content delivery and serving a

Eskwai for Students: Generative AI Assistant for Legal Education in Ghana

arXiv:2605.15380v1 Announce Type: new Abstract: Recent advances in generative AI have shown their potential to be leveraged for legal education. Yet, work on the development and deployment of such sys

safetyarxiv-cs-cl

IndicSafe: A Benchmark for Evaluating Multilingual LLM Safety in South Asia

arXiv:2603.17915v2 Announce Type: replace-cross Abstract: As large language models (LLMs) are deployed in multilingual settings, their safety behavior in culturally diverse, low-resource languages rem

NavRL++: A System-Level Framework for Improving Sim-to-Real Transfer in Reinforcement Learning-Based Robot Navigation

arXiv:2605.15559v1 Announce Type: new Abstract: Recent years have witnessed significant progress in autonomous navigation using reinforcement learning. However, existing approaches largely emphasize r

safetyarxiv-cs-ro

Perforated Neural Networks for Keyword Spotting

model-releasesarxiv-cs-lg

arXiv:2605.15647v1 Announce Type: new Abstract: Edge machine learning presents a unique set of constraints not encountered in cloud-scale model deployment: strict memory budgets, limited compute, and

Quantization Undoes Alignment: Bias Emergence in Compressed LLMs Across Models and Precision Levels

arXiv:2605.15208v1 Announce Type: cross Abstract: Large Language Models are routinely compressed via post-training quantization to reduce inference costs and memory footprint for cloud and edge deploy

Hardware

An Amortized Efficiency Threshold for Comparing Neural and Heuristic Solvers in Combinatorial Optimization

arXiv:2605.14624v1 Announce Type: cross Abstract: A common critique of neural combinatorial-optimization solvers is that they are less energy-efficient than CPU metaheuristics, given the operational e

hardwarearxiv-cs-ai

Evolving Layer-Specific Scalar Functions for Hardware-Aware Transformer Adaptation

arXiv:2605.14047v1 Announce Type: new Abstract: Vision Transformers (ViTs) achieve state-of-the-art performance on challenging vision tasks, but their deployment on edge devices is severely hindered b

safetyarxiv-cs-cv

PREPING: Building Agent Memory without Tasks

arXiv:2605.13880v1 Announce Type: new Abstract: Agent memory is typically constructed either offline from curated demonstrations or online from post-deployment interactions. However, regardless of how

agentsarxiv-cs-ai

Rethinking Output Alignment For 1-bit Post-Training Quantization of Large Language Models

arXiv:2512.21651v2 Announce Type: replace Abstract: Large Language Models (LLMs) deliver strong performance across a wide range of NLP tasks, but their massive sizes hinder deployment on resource-cons

AI Safety Landscape for Large Language Models: Taxonomy, State-of-the-art, and Future Directions

arXiv:2408.12935v4 Announce Type: replace Abstract: AI Safety is an emerging area of critical importance to the safe adoption and deployment of AI systems. With the rapid proliferation of AI and espec

History Anchors: How Prior Behavior Steers LLM Decisions Toward Unsafe Actions

arXiv:2605.13825v1 Announce Type: new Abstract: Frontier LLMs are increasingly deployed as agents that pick the next action after a long log of prior tool calls produced by the same or a different mod

TRIAGE: Evaluating Prospective Metacognitive Control in LLMs under Resource Constraints

arXiv:2605.13414v1 Announce Type: new Abstract: Deploying language models as autonomous agents requires more than per-task accuracy: when an agent faces a queue of problems under a finite token budget

agentsarxiv-cs-ai

When to Act, Ask, or Learn: Uncertainty-Aware Policy Steering

arXiv:2602.22474v2 Announce Type: replace-cross Abstract: Policy steering is an emerging way to adapt robot behaviors at deployment-time: a learned verifier analyzes low-level action samples proposed

Applications

AESOP: Adversarial Execution-path Selection to Overload Deep Learning Pipelines

arXiv:2605.10987v1 Announce Type: new Abstract: Modern machine learning deployments increasingly compose specialized models into dynamic inference pipelines, where upstream components produce intermed

applicationsarxiv-cs-lg

13 May 2026

Tutorials

A Semantic-Sampling Framework for Evaluating Calibration in Open-Ended Question Answering