Search: “deployment”

GUIDER: Evaluating Goal-Free Human Intent Inference for Teleoperated Manipulation on Real-Robot Data

arXiv:2608.15446v1 Announce Type: new Abstract: This paper presents an evaluation of a goal-free probabilistic framework for human intent inference during robotic manipulation. We deploy the Global Us

applicationsarxiv-cs-ro

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Safety

Identifying Confusion Trends in Concept-based XAI for Multi-Label Classification

DGX agent

arXiv:2608.15731v1 Announce Type: cross Abstract: Deep Neural Networks (DNNs) deployed in high-risk domains, such as healthcare and autonomous driving, must be not only accurate but also understandabl

safetyarxiv-cs-ai

18 Aug 2026

Inferential Evaluation of Surrogate-Derived Models under Covariate Shift

arXiv:2608.15783v1 Announce Type: cross Abstract: In transfer-learning settings, a model derived from abundant surrogate labels may be deployed in a target population where gold-standard outcomes are

Invariant Pretraining for Robust Code Representations

arXiv:2608.15412v1 Announce Type: cross Abstract: Encoder-based code representation models remain widely deployed for discriminative tasks such as clone detection and code classification, where their

LAPF: LLM-Agent-Based Path Finder Using the UAVScenes Dataset

arXiv:2608.15175v1 Announce Type: cross Abstract: Uncrewed aerial vehicles (UAVs) are increasingly deployed for autonomous navigation in complex outdoor environments, where dynamic conditions and miss

agentsarxiv-cs-ai

Learning Agent Execution for KV-Cache Management in Agentic Serving

arXiv:2608.14624v1 Announce Type: new Abstract: Multi-agent LLM systems have emerged as an important deployment paradigm for AI services, where each user request is decomposed into a sequence of speci

agentsarxiv-cs-ai

Listen, Reason, and Segment: Aligning LALMs with Editorial Judgment for Media Chapterization

arXiv:2608.16539v1 Announce Type: cross Abstract: Large Audio Language Models (LALMs) have made rapid progress on standardized benchmarks, yet their deployment in practical media workflows, curation,

LLMs Can Predict Failure Risk, But Struggle to Predict Which Collaboration Protocol Pays Off: Cost-Aware Protocol Routing Across Reasoning Tasks

arXiv:2608.14927v1 Announce Type: new Abstract: Multi-agent large language model (LLM) systems can improve reasoning by spending more computation, but deployment requires deciding when extra collabora

Measuring Obedience to Authority Across Large Language Models with the Milgram Paradigm

arXiv:2608.16177v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as agents that operate equipment, execute instructions, and act inside institutional hierarchie

Tutorials

NebulaVLA: A Dual-Frequency Vision-Language-Action Model With Guide Action for Robotic Manipulation

arXiv:2608.16503v1 Announce Type: cross Abstract: Real-world deployment of Vision-Language-Action (VLA) models is often bottlenecked by efficiency-performance trade-offs, cross-embodiment generalizati

tutorialsarxiv-cs-ai

OGX: An Open-Source, Vendor-Neutral Generative AI Application Server

arXiv:2608.14580v1 Announce Type: new Abstract: OGX (Open GenAI Stack) is an open-source AI application server and Python library that implements the APIs of major frontier labs (OpenAI, Anthropic, Go

PERO: Efficient Robust Post-Training Foundation Models for Encrypted Traffic Classification

arXiv:2608.15504v1 Announce Type: new Abstract: Encrypted traffic classification is vital for network security, yet real-world deployments are inherently sensitive to rare but high-loss errors such as

applicationsarxiv-cs-lg

S2-MoE: Enabling Efficient Self-Speculative Decoding for Mixture-of-Experts on Edge Devices

arXiv:2608.15018v1 Announce Type: new Abstract: Deploying large language models (LLMs) for inference on edge devices is challenging due to severe memory and bandwidth constraints. While speculative de

S^3: A Smooth Simulation Surrogate for Optimizing Discrete Abstractions of Dynamical Systems

arXiv:2608.15920v1 Announce Type: cross Abstract: Intelligent systems are increasingly deployed in safety-critical settings with black-box controllers, including neural networks. The properties and be

SchurQuant: Groupwise Discrete Optimization for Layer-Wise LLM Quantization

model-releasesarxiv-cs-lg

arXiv:2608.15567v1 Announce Type: new Abstract: Weight-only post-training quantization (PTQ) enables the deployment of large language models under tight memory budgets, but accuracy often collapses at

Semantic Bandits: In-Context Exploration-Exploitation is Biased by Semantic Priors

arXiv:2608.16707v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as decision-making agents in settings that require sophisticated environmental exploration. How

SoftModel: A Neural Model That Grows Its Own Topology -- Governed Structural Growth for Continual In-Service Learning

arXiv:2608.16409v1 Announce Type: new Abstract: Today, a neural system is almost always used in two phases -- trained, then deployed -- and in that regime it freezes twice: training ends, and the topo

applicationsarxiv-cs-lg

Topological Attribution Distance (TAD): Revealing Segment-Level RAG Influence on LLM Output Geometry for Incident Log Analysis

arXiv:2608.16775v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly being deployed in cybersecurity operations to assist cybersecurity analysts with rapid decision-making a

agentsarxiv-cs-ai

Toward Better Assessment of LLMs' Performance in Clinical Error Detection

arXiv:2608.16643v1 Announce Type: cross Abstract: Automated detection of errors in clinical documentation is a promising application of large language models (LLMs), yet decisions to deploy such model

UI-Mate: Advancing Open-Weight Foundation GUI Agents with In-Context Demonstrations

arXiv:2608.15930v1 Announce Type: new Abstract: Foundation GUI agents can automate complex digital tasks, but deployment is hindered by scarce and biased training data, ambiguous prompts, and unreliab

Validation-Frontier Representation Selection under Constrained Observation

arXiv:2608.15095v1 Announce Type: new Abstract: AI systems deployed outside clean benchmark settings often rely on observations that are incomplete, unstable, costly, or degraded by monitoring failure

Ventor-QTest: Threat-Model-Driven Verification of Vendor-Hosted LLM APIs

arXiv:2608.16391v1 Announce Type: cross Abstract: As large language models become increasingly widespread, third-party providers that deploy open-weight models have become an important part of the eco

ViTaR: Visuo-Tactile Residual Adaptation for Foundation VLA Manipulation

model-releasesarxiv-cs-ro

arXiv:2608.15816v1 Announce Type: new Abstract: As Vision-Language-Action (VLA) models scale toward real-world deployment, contact-rich manipulation exposes a critical blind spot: these policies encod

Writing Style Similarity Reflects Academic Genealogy

arXiv:2608.14843v1 Announce Type: cross Abstract: As authorship attribution systems are increasingly deployed to detect ghostwritten and AI-generated papers, their errors can support accusations again

X^2Localizer: Cross-grained Alignment for Progressive Cross-view Video Geo-localization

arXiv:2608.16658v1 Announce Type: cross Abstract: Cross-view Video Geo-localization (CVG) aims to localize ground-view videos by retrieving their corresponding geo-tagged aerial images. However, CVG a

zLend: A Dual-Scope Cash-Flow Reconstruction Framework for On-Chain Credit Underwriting

model-releasesarxiv-cs-lg

arXiv:2608.16856v1 Announce Type: cross Abstract: Decentralized lending lacks a credit bureau: a borrower's capacity to repay must be inferred entirely from public on-chain activity, without income ve

AgilePE: Autonomous UAV Pursuit-Evasion via Self-Play Reinforcement Learning

arXiv:2608.14135v1 Announce Type: cross Abstract: Autonomous pursuit-evasion is a fundamental challenge for Unmanned Aerial Vehicles (UAVs), requiring rapid decision-making under tightly coupled dynam

Tutorials

CipherSight: Robust Website Fingerprinting via Record-Resource Semantic Supervision under Distribution Shifts

arXiv:2608.13905v1 Announce Type: cross Abstract: HTTPS website fingerprinting (WF) aims to identify visited websites from metadata observable in encrypted traffic. However, real-world deployments int

tutorialsarxiv-cs-ai

CPI-Bench: A Comprehensive,Practical and Intelligent Benchmark for Real-World Image Editing

model-releasesarxiv-cs-cv

arXiv:2608.14546v1 Announce Type: new Abstract: With the rapid advancement of image editing models and their widespread application across various domains, there is an increasingly urgent need to depl

Effective Game-Theoretic Motion Planning via Nested Search

arXiv:2511.08001v3 Announce Type: replace Abstract: To facilitate effective, safe deployment in the real world, individual robots must reason about interactions with other agents, which often occur wi

agentsarxiv-cs-ro

Ensuring Safe Physical AI in Urban Mobility via Hazard-Informed Synthesized Envelopes

arXiv:2608.14481v1 Announce Type: cross Abstract: As heterogeneous robotic systems deploy across diverse urban zones, maintaining safety amid complex human-robot interactions remains a critical challe

MACS: A Hybrid Multi-Agent Framework for Reliable Conversational E-Commerce Recommendation

arXiv:2608.14068v1 Announce Type: cross Abstract: Conversational recommendation for e-commerce is increasingly mediated by large language models (LLMs), yet many real-world deployments operate under a

Simulation-Driven Vehicular Traffic Data Augmentation: Extending Sensor Coverage Through Virtual Sensing

arXiv:2608.13993v1 Announce Type: new Abstract: Urban traffic management relies on sensor networks whose spatial coverage is limited by deployment costs and privacy regulations. Machine learning model

Unknown Unknowns: Model Misspecification in Machine Learning for Physics

arXiv:2608.13633v1 Announce Type: cross Abstract: Machine learning is now a central tool for solving inverse problems in particle physics and astronomy. Models are trained on simulation and deployed o

researcharxiv-cs-lg

Beyond the Best Guess: Improving LLM Solution Coverage with Evolution Strategies

arXiv:2608.12679v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in discovery domains such as math and science. The usual approach is to present the problem to th

DIVE: Unlocking Self-Improvement in Frozen Language Models Through Diversity-Driven Skill Evolution

model-releasesarxiv-cs-cl

arXiv:2608.12486v1 Announce Type: new Abstract: Large language models (LLMs) cannot retain post-deployment experience without parameter updates. We introduce DIVE, a diversity-driven framework that en

Do LLMs Beat Nash? Testing Decentralized Coordination in Self-Play Multi-Agent Games

model-releasesarxiv-cs-ro

arXiv:2608.12547v1 Announce Type: cross Abstract: Large language model agents deployed without a central controller are often assumed to require communication to coordinate their actions. We ask what

Entropy-Augmented Multi-Objective Policy Optimization in Multiagent Systems

arXiv:2608.12534v1 Announce Type: cross Abstract: Autonomous agent teams deployed in settings such as marine and extraterrestrial outposts must coordinate actions to achieve optimal outcomes across mu

safetyarxiv-cs-ro

Large Language Models Can Follow Instructions, But Not Many at Once: Phase Transitions in Compositional Constraint Satisfaction

arXiv:2608.12426v1 Announce Type: new Abstract: Large language models are increasingly deployed in settings that require simultaneous adherence to multiple explicit constraints - reasoning structure,

MOSAIC: Unveiling the Moral, Social and Individual Dimensions of Large Language Models

arXiv:2603.00048v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly deployed in sensitive applications including psychological support, healthcare, and high-stakes

Noise as a Probe: Membership Inference Attacks on Diffusion Models Leveraging Initial Noise

arXiv:2601.21628v2 Announce Type: replace-cross Abstract: Diffusion models have achieved remarkable progress in image generation, but their increasing deployment raises serious concerns about privacy

researcharxiv-cs-lg

ProME: Prototype-Margin Environments with Repair-Aware Selection for Group-Robust Learning

arXiv:2608.13190v1 Announce Type: cross Abstract: Group-robust learning is crucial for maintaining accuracy on rare subpopulations when training-group labels are unavailable. However, existing methods

safetyarxiv-cs-cv

PseudoMapLabeler: Confidence-Aware Pseudo-Label Generation for Semi-Supervised Online Mapping

arXiv:2608.12600v1 Announce Type: cross Abstract: A critical challenge in deploying online HD map construction systems to real-world scenarios is the scarcity of labeled training data, which limits mo

applicationsarxiv-cs-ai

Regulatory Approval Is Not Enough: Gaps in Trustworthy AI Reporting in FDA-Cleared Medical Devices

arXiv:2608.12360v1 Announce Type: cross Abstract: Background: AI/ML-enabled medical devices are increasingly deployed in healthcare under evolving regulatory frameworks. As these systems become more i

Rules or Character? Scaling Laws for AI Safety Design

arXiv:2608.13345v1 Announce Type: new Abstract: Artificial Intelligence (AI) safety systems combine character shaping (e.g., Reinforcement Learning from Human Feedback [RLHF], Constitutional AI), whic

SPARED: Reasoning-Based AI-Generated Image Detection via Adversarially Edited Data

arXiv:2608.12876v1 Announce Type: cross Abstract: Detecting AI-generated images is only half the task: a deployed detector must also justify its verdict, yet existing detectors inherit three failure m

Statistical Properties of Robust Learning under Distributional Shifts

arXiv:2608.13133v1 Announce Type: cross Abstract: Distributional shifts arise when the target deployment environment differs from the source environment that generated the training data. Robust learni

researcharxiv-cs-lg

Synthetic Persona Pretraining: Alignment from Token Zero

arXiv:2608.13482v1 Announce Type: cross Abstract: As language-model-based AI is increasingly deployed in autonomous settings, aligning its goals and values with those of humans becomes critical. Today