Search: “deployment”

PersuaRL: Reinforcement Learning-Driven Multi-Expert Selection for Persuasive Dialogue Generation in Insurance

arXiv:2609.01188v1 Announce Type: new Abstract: Large Language Models (LLMs) are revolutionizing digital communication by powering conversational agents deployed across domains such as customer servic

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Probabilistic Model Checking of Autoregressive Neural Sequence Models

DGX agent

arXiv:2609.00838v1 Announce Type: cross Abstract: Test-set accuracy is silent on two issues that matter when deploying autoregressive neural sequence models: how much probability mass the system under

researcharxiv-cs-ai

2 Sept 2026

REAL-Q: E2E LLM Quantization via Dynamic Gradient Descent

arXiv:2609.00049v1 Announce Type: cross Abstract: Post-training quantization (PTQ) is essential for deploying large language models (LLMs) under strict resource constraints. State-of-the-art PTQ metho

Selective Agent Guidance via Entropy: Learning Autonomous Policies from Imperfect VLM Teachers

arXiv:2609.01567v1 Announce Type: new Abstract: Vision-Language Models (VLMs) provide useful priors for interactive decision-making, but using them directly as policies is expensive and brittle: they

VoiceLongMemEval: Do Assistants Remember How You Sounded?

arXiv:2609.00570v1 Announce Type: new Abstract: With the growing scale of multi-agent architectures and large language models, deployed AI assistants are increasingly tasked with reasoning over long,

WiSDoM: Wireless Sparse Decision Transformer with Mixture-of-Experts for Multi-Task Mobile Network Optimization

arXiv:2609.00284v1 Announce Type: cross Abstract: Emerging 6G wireless networks are expected to operate across diverse deployment scenarios, where variations in network topology, user mobility, traffi

Zero Hallucination, by Construction: Hallucination-Aware Layered Oversight for Trustworthy Enterprise AI

arXiv:2607.17883v2 Announce Type: replace-cross Abstract: Enterprises will not deploy AI agents they cannot trust, and the most-cited reason for distrust is hallucination: confident, fluent output tha

applicationsarxiv-cs-ai

A Degradation-Tolerance Benchmark for Camera-Only End-to-End Driving

model-releasesarxiv-cs-ro

arXiv:2608.29005v1 Announce Type: new Abstract: Camera-only end-to-end (E2E) driving models are nearing deployment, where the camera stream is degraded by blur, noise, low light, weather, frame loss,

AdaptAV: Continuous Adaption of Vision Models for Autonomous Vehicles Using Cloud-based Oracle

arXiv:2608.28673v1 Announce Type: new Abstract: Deploying vision perception models in autonomous vehicles requires that we prioritize inference speeds, resulting in a model with shallower architecture

agentsarxiv-cs-cv

ALTSTEER: Selective Safety Steering for Moving Beyond Hard Refusals to Constructive Alternatives

arXiv:2608.30197v1 Announce Type: new Abstract: Safety alignment is essential for deploying large language models, requiring systems to prevent harmful compliance while preserving helpfulness on benig

Beyond Fluency: A Rubric-Based Benchmark for Evaluating Saudi Dialect and Cultural Competence in Large Language Models

arXiv:2608.29990v1 Announce Type: cross Abstract: Large language models are increasingly deployed in Arabic-speaking markets, yet standard benchmarks overwhelmingly reward Modern Standard Arabic (MSA)

Beyond the Final Layer: Intermediate Representations for Better Multilingual Calibration in Large Language Models

arXiv:2510.03136v2 Announce Type: replace Abstract: Confidence calibration, the alignment of a model's predicted confidence with its actual accuracy, is crucial for the reliable deployment of Large La

BiG-SURE - Bipartite Graph for Semantic Uncertainty and Reliability Estimation of LLMs

arXiv:2608.30646v1 Announce Type: cross Abstract: Reliable uncertainty estimation is a crucial requirement for deploying large language models (LLMs) and vision-language models (VLMs) in safety-critic

Budget-Aware Compression Pipeline for Single-GPU LLM Inference: Methods, Trade-offs, and Coupling Effects

arXiv:2608.30076v1 Announce Type: new Abstract: Single-GPU deployment of 70B-parameter language models on an NVIDIA GPU is constrained by device memory, long-context throughput, and engineering integr

Research

Capability-Stratified Degradation in Ternary Language Models

arXiv:2608.28809v1 Announce Type: new Abstract: Extreme low-bit inference offers a route toward smaller models and constrained deployment. Ternary language models restrict weights to {-1,0,+1}, approa

researcharxiv-cs-ai

CAST: Critique-Aware Supervision for Training Reliable Long-Horizon Tool-Calling Agents

arXiv:2608.30147v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly deployed in long-horizon, interactive, and stateful environments. In these settings, a single wrong a

Defining Operational Conditions for Safety-Critical AI-Based Systems from Data

arXiv:2601.22118v3 Announce Type: replace Abstract: Artificial Intelligence (AI) has been on the rise in many domains, including numerous safety-critical applications. However, for complex systems in

Research

Do LLMs Change Their Minds Like Humans? Diagnosing Human--LLM Divergence in Single-Turn Persuasion Judgments

arXiv:2608.29803v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as proxies for human participants in social simulations, yet whether they update their beliefs

researcharxiv-cs-cl

Failure or Drift? Evaluating Monocular SLAM under Synthetic and Real-World Corruptions

arXiv:2608.30690v1 Announce Type: new Abstract: Visual SLAM is commonly evaluated on clean trajectories, although deployment failures are often caused by adverse weather, illumination, blur, and senso

applicationsarxiv-cs-cv

Fine-Grained Multi Image Object Hallucination Benchmark

arXiv:2608.30653v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) are increasingly deployed in multi-image scenarios requiring complex reasoning across visual contexts. Howeve

Foundation Models Meet Agriculture: Challenges Beyond Pretraining

arXiv:2608.30392v1 Announce Type: new Abstract: Global food security and sustainable climate action increasingly rely on robust, scalable agricultural monitoring. Earth observation foundation models h

applicationsarxiv-cs-lg

GATE: Reliability-Gated Gaussian Evidence Fusion for Training-Free Test-Time Adaptation of Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2608.29395v1 Announce Type: new Abstract: Vision-language models such as CLIP and SigLIP provide strong zero-shot recognition, but their predictions can degrade when deployed on target data that

HEAR Who Said What: Unlocking Speaker-Attributed Reasoning via Counterfactual Voice Grounding

arXiv:2608.29120v1 Announce Type: cross Abstract: Speech Language Models (SLMs) are increasingly deployed in multi-speaker environments, yet their ability to attribute speech to the correct speaker an

How we eliminated $1 million a year of wasted AI agent spend in one hour

The post explains how a quick, one‑hour audit of AI agent usage revealed $1 million per year in avoidable spend. By reviewing deployment patterns and trimming unnecessary calls, the team reallocated r

agentsdatabricks

Interactive Clarification for Cloud Infrastructure-as-Code Synthesis

arXiv:2604.02382v2 Announce Type: replace-cross Abstract: The scale and complexity of modern cloud infrastructure have made 'Infrastructure-as-Code' (IaC) essential for managing deployments through de

Introducing TabFM in BigQuery: Predictive analytics reimagined

model-releasesgoogle-cloud-ai

Historically, enterprise predictive analytics tasks such as predicting churn, purchase intent, or fraud scoring have meant building custom models using libraries like XGBoost, Random Forest, or Deep N

Learning diverse attacks on large language models for robust red-teaming and safety tuning

arXiv:2405.18540v3 Announce Type: replace Abstract: Red-teaming, or identifying prompts that elicit harmful responses, is a critical step in ensuring the safe and responsible deployment of large langu

LLM Post-Training as Brownfield Maintenance: An Industrial Perspective on Dataware Engineering

arXiv:2608.31102v1 Announce Type: cross Abstract: Industrial post-training is a brownfield regime. Teams inherit a deployed checkpoint and must land targeted improvements under fixed compute and mixtu

Open-Set Cattle Muzzle Identification: A Leakage-Controlled Benchmark and Evaluation Protocol

model-releasesarxiv-cs-cv

arXiv:2608.28663v1 Announce Type: new Abstract: Reliable individual cattle identification supports disease surveillance, vaccination records, breeding management, and livestock insurance. Although the

Open-Source Autonomous Driving System Analysis and Multi-Disciplinary Hardware-in-the-Loop Research Paradigm with Reinforcement-Learning Testing and Large Language Models

arXiv:2608.30179v1 Announce Type: cross Abstract: Open-source autonomous driving systems provide an inspectable software foundation for intelligent vehicle research. Under real-vehicle deployment cond

agentsarxiv-cs-ro

Operationalising AI Regulatory Sandboxes: Activities, Requirements, and Technical Assessment under the EU AI Act

arXiv:2509.25256v4 Announce Type: replace-cross Abstract: The systematic assessment of AI systems is increasingly vital as these technologies enter high-stakes domains. To address this, the EU's Artif

Local Ai

OptiGeo: Efficient Monocular Geometry for Embodied Perception in Optically Challenging Scenes

arXiv:2608.29881v1 Announce Type: new Abstract: Monocular depth estimation has achieved strong open-domain generalization, yet reliable robotic deployment remains difficult in transparent, reflective,

local-aiarxiv-cs-cv

PAVE: Predictive Alignment and Value-Guided Evolution for World-Action Policies

arXiv:2608.30378v1 Announce Type: cross Abstract: Direct vision-language-action policies generate continuous robot actions efficiently, but standard behavior cloning leaves two complementary gaps: the

Political Ideology Shifts in Large Language Models

arXiv:2508.16013v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed in politically sensitive contexts, raising concerns about their susceptibility to ideological

Scale-Plan: Scalable Language-Enabled Task Planning for Heterogeneous Multi-Robot Teams

arXiv:2603.08814v2 Announce Type: replace-cross Abstract: Long-horizon task planning for heterogeneous multi-robot systems is essential for deploying collaborative teams in real-world environments; ye

Selection, Representation, and Execution in Sparse Fourier Neural Operators

model-releasesarxiv-cs-lg

arXiv:2608.30070v1 Announce Type: new Abstract: Sparse representations are often expected to make models smaller and also reduce inference cost. For Fourier Neural Operators (FNOs), these objectives a

SingProbe Technical Report

arXiv:2608.30703v1 Announce Type: cross Abstract: Runtime guardrails are essential for reliable large language model (LLM) deployment, yet existing approaches typically rely on independent, external m

SkillRet: A Large-Scale Benchmark for Skill Retrieval in LLM Agents

arXiv:2605.05726v2 Announce Type: replace Abstract: As LLM agents are increasingly deployed with large libraries of reusable skills, selecting the right skill for a user request has become a critical

Super Library Agent: Joint Generation and Maintenance of Multiple Applications Beyond the Single Codebase

arXiv:2608.29310v1 Announce Type: cross Abstract: Organizations often develop and maintain portfolios of related applications: independently deployable codebases that share substantial domain logic, i

agentsarxiv-cs-ai

Terminal-Bench-LILT: Multilingual Agentic Coding Benchmark Grounded in Language, Region, and Culture

arXiv:2608.28641v1 Announce Type: cross Abstract: Most evaluations for coding agents are conducted exclusively in English, which does not reflect real-world multilingual deployment. We present Termina

The Differential Reasoning Router: Operationalizing Cost-Aware LLM Annotation in E-commerce

arXiv:2608.30224v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used to annotate structured product data in e-commerce, but early deployment often begins as a cold-star

applicationsarxiv-cs-ai

Training-Free Action Correction for VLA Model Failures via Language Feedback

arXiv:2608.29967v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models demonstrate strong semantic understanding yet exhibit systematic failures during deployment. The conditions under

UFPR-PEs: A Brazilian Face Recognition Benchmark with Self-Declared Race/Color Labels

model-releasesarxiv-cs-cv

arXiv:2608.30688v1 Announce Type: new Abstract: While face recognition systems are widely deployed, ensuring their demographic reliability and robustness under uncontrolled visual conditions remains a

When the Martingale Never Stops Firing: Anytime-Valid Gating on Real Forecast Streams

arXiv:2608.30502v1 Announce Type: new Abstract: Machine learning systems are increasingly corrected while they run, and the decision of when to intervene is increasingly delegated to statistical monit

applicationsarxiv-cs-lg

When to Adapt: Conditional Memory Adapters for Retention-Preserving Domain Specialization

arXiv:2608.29327v1 Announce Type: new Abstract: Large language models deployed in specialized domains must improve in-domain performance without sacrificing general capabilities. Existing parameter-ef

AI Alignment through a Game-theoretic Lens: A Survey

arXiv:2608.27910v1 Announce Type: cross Abstract: As large language models and increasingly capable AI agents are deployed in high-risk settings, aligning them with complex human values has become a c

31 Aug 2026

Local Ai

Beyond Non-IID: Learner--Client Distribution Mismatch in Federated Learning

arXiv:2608.27715v1 Announce Type: new Abstract: Federated learning systems are increasingly deployed to facilitate collaborative model training across a heterogeneous client population. Existing pract

local-aiarxiv-cs-lg

31 Aug 2026

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