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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

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

DGX agent

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

1 Sept 2026

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

model-releasesarxiv-cs-cl

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

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

Connect an AgentCore Runtime hosted MCP server to Amazon Quick

In this post, you will learn how to deploy and host your MCP server in AgentCore Runtime and integrate it with Amazon Quick, along with the prerequisites. With this pattern, you promote reusability an

agentsaws-ml-blog

Cooperative Risk-Aware Exploration in Heterogeneous Multi-Robot Systems Using Algorithmic Altruism

arXiv:2608.28409v1 Announce Type: new Abstract: Multi-robot systems are well-positioned for exploration in hazardous environments, but effective deployment requires deciding not only where robots shou

agentsarxiv-cs-ro

Efficient Online Continual Foundation Model Fine-Tuning for Predictive Process Monitoring

arXiv:2608.28237v1 Announce Type: new Abstract: Predictive Process Monitoring (PPM) models are increasingly deployed in dynamic environments where concept drift causes the underlying process distribut

applicationsarxiv-cs-lg

FENCE: A Financial and Multimodal Jailbreak Detection Dataset

arXiv:2602.18154v3 Announce Type: replace Abstract: Jailbreaking poses a significant risk to the deployment of Large Language Models (LLMs) and Vision Language Models (VLMs). VLMs are particularly vul

Hierarchical Feature-level Reverse Propagation for Post-Training Neural Networks

arXiv:2506.07188v2 Announce Type: replace Abstract: End-to-end neural networks have become a dominant paradigm in autonomous driving, where reliable deployment requires controllable post-training adap

agentsarxiv-cs-cv

How I got Qwen 3.8 27b running at ~75t/s decode on 16GB RTX 5080

model-releasesr-localllama

Hi all, I have recently been experimenting with different LLM set ups and after everyone was raving about how good Qwen 3.8 27b was, I was inspired to try and get it deploying. After some battling wit

Receding Fixed-Horizon Optimization for Near-Time-Optimal Trajectory Planning and Control

arXiv:2503.11072v4 Announce Type: replace Abstract: Time-optimal trajectory planning and control is central for autonomous vehicles, yet its application and real-time deployment confronts two fundamen

agentsarxiv-cs-ro

Steering Multimodal Large Language Models Decoding for Context-Aware Safety

arXiv:2509.19212v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) are increasingly deployed in real-world applications, yet their ability to make context-aware safety decisi

Local Ai

TACIT-Switch: Cost-Aware Model Escalation for LLM Agents from Censored Supervision

arXiv:2608.27911v1 Announce Type: new Abstract: Agents with smaller language-model backbones are less expensive but can drift into persistent failure modes, whereas those with larger backbones are gen

local-aiarxiv-cs-lg

Research

TokenPilot: Cache-Efficient Context Management for LLM Agents

arXiv:2606.17016v2 Announce Type: replace Abstract: As LLM agents are deployed in long-horizon sessions, context accumulation drives up inference costs. Existing approaches utilize text pruning or dyn

researcharxiv-cs-cl

ToolSense: A Diagnostic Framework for Auditing Parametric Tool Knowledge in LLMs

model-releasesarxiv-cs-lg

arXiv:2606.12451v2 Announce Type: replace-cross Abstract: Large language models deployed as agents over large tool catalogs face a critical tool-retrieval bottleneck. As embedding-based retrieval appr

uScenes: A Multimodal RGB and 3D Sonar Dataset for Underwater Robot Perception

arXiv:2608.27795v1 Announce Type: new Abstract: Robust perception is essential for the deployment of autonomous underwater robots. However, optical cameras become unreliable under poor illumination an

agentsarxiv-cs-cv

ADeptS-Bench: Measuring the Trustworthiness of Computer Use Agents Across Devices

arXiv:2608.26204v1 Announce Type: cross Abstract: Computer Use Agents (CUAs) are increasingly deployed to navigate mobile and desktop applications on behalf of users, yet no benchmark comprehensively

Counterfactual Bias Testing for Application Tracking System

arXiv:2608.26899v1 Announce Type: new Abstract: Automated candidate-job matching systems are increasingly classified as high-risk AI under emerging regulation, yet auditing them for demographic bias i

Diagnosing Conformal Prediction Failures Under Distribution Shift: A COVID-19 Case Study

arXiv:2601.00908v2 Announce Type: replace-cross Abstract: Conformal prediction provides distribution-free coverage guarantees, but these degrade under distribution shift - and practitioners lack tools

applicationsarxiv-cs-ai

Do LLMs Understand Personality? Rethinking Persona Fidelity Evaluation through Structured Behavioral Inference

arXiv:2608.26674v1 Announce Type: cross Abstract: As large language models are increasingly deployed to simulate diverse human characters, ensuring persona fidelity, defined as the extent to which an

agentsarxiv-cs-ai

DRL: A Deterministic Relational Middleware Layer for Transaction-Safe Enterprise NL2SQL Under Schema-Graph Scaling

arXiv:2608.26172v1 Announce Type: cross Abstract: Deploying natural-language interfaces over enterprise OLTP catalogs fails at scale because semantic parsers collapse under schema-graph scaling, infla

Evaluating Language Models in Realistic Conversational Contexts

model-releasesarxiv-cs-cl

arXiv:2608.26131v1 Announce Type: new Abstract: As Large Language Models (LLMs) are increasingly deployed to serve open-ended, multi-turn interactions, evaluating conversational quality at human scale