Search: “deployment”

TabSwift: An Efficient Tabular Foundation Model with Row-Wise Attention

arXiv:2606.07345v1 Announce Type: new Abstract: Tabular foundation models, exemplified by TabPFN, perform prediction via in-context learning, inferring test labels directly from labeled training examp

8 Jun 2026

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Safety

Towards AI epidemiology: a measurement standardisation framework for prospective risk detection

DGX agent

arXiv:2512.15783v3 Announce Type: replace Abstract: This paper proposes a measurement standardisation framework that compresses expert-AI interactions into structured, comparable fields for prospectiv

safetyarxiv-cs-ai

6 Jun 2026

Will the Agent Recuse Itself? Measuring LLM-Agent Compliance with In-Band Access-Deny Signals

arXiv:2606.06460v1 Announce Type: cross Abstract: As autonomous LLM agents increasingly hold real credentials and operate infrastructure without a human in the loop, operators have no standard way to

6 Jun 2026

Drishti AI-Event Guardian: An Intelligent Real-Time Crowd Monitoring and Emergency Response System for Mass Gathering Events

arXiv:2606.05185v1 Announce Type: cross Abstract: Mass gathering events are associated with critical safety incidents caused by insufficient crowd monitoring and inadequate emergency response coordina

safetyarxiv-cs-cv

5 Jun 2026

LiAuto-GeoX: Efficient Grounded Driving Transformer

arXiv:2606.05774v1 Announce Type: new Abstract: Dense 3D reconstruction has demonstrated immense potential for spatial understanding, yet its viability as a real-time, onboard representation for auton

5 Jun 2026

LightVesselNet: An Ultra-Lightweight Sub-100K Parameter Network for Retinal Blood Vessel Segmentation

arXiv:2606.05354v1 Announce Type: new Abstract: Retinal blood vessel segmentation plays a vital role in the early detection of diabetic retinopathy and glaucoma. While recent deep learning models have

5 Jun 2026

Agents

Archi: Agentic Operations at the CMS Experiment

arXiv:2606.04755v1 Announce Type: cross Abstract: We present Archi, an open-source, end-to-end framework for scientific collaborations that combines the systematic ingestion and organization of hetero

agentsarxiv-cs-ai

CDPM-Align: Multi-Scale Guidance-Aligned Diffusion Pretraining for Robust Few-Shot Anatomical Landmark Detection

arXiv:2606.04898v1 Announce Type: new Abstract: Anatomical landmark detection is a fundamental task in medical image analysis supporting a wide range of diagnostic and interventional workflows. Althou

Generalization of World Models under Environmental Variability for Vision-based Quadrotor Navigation

arXiv:2606.05015v1 Announce Type: new Abstract: World models, learned generative models that predict how an environment evolves, have become a promising tool for sample-efficient robot learning. Yet h

safetyarxiv-cs-ro

GRAIL: Generating Humanoid Loco-Manipulation from 3D Assets and Video Priors

arXiv:2606.05160v1 Announce Type: new Abstract: Scaling humanoid loco-manipulation requires robot-compatible demonstrations across diverse objects, whole-body motions, and scene geometries, but teleop

applicationsarxiv-cs-ro

Not All Errors Are Equal: Consequence-Aware Reasoning Compute Allocation

arXiv:2606.04402v1 Announce Type: new Abstract: Modern reasoning models can allocate different amounts of test-time computation, such as thinking tokens, model calls, or compute budget, to different t

Safety Under Scaffolding: How Evaluation Conditions Shape Measured Safety

arXiv:2603.10044v2 Announce Type: replace-cross Abstract: A safety score earned on a benchmark need not predict how the same model behaves once it is wrapped in an agentic scaffold the benchmark never

STaR-Quant: State-Time Consistent Post-Training Quantization for Diffusion Large Language Models

arXiv:2606.04945v1 Announce Type: new Abstract: Diffusion large language models (DLLMs) have recently emerged as a promising alternative to autoregressive LLMs by generating text through iterative mas

When Offline Selectors Cannot Beat the Best Single Model: A Diagnostic Study on edX Dropout Prediction

arXiv:2606.04161v1 Announce Type: new Abstract: Different predictors often excel on different inputs, so picking the best one per instance promises higher accuracy than committing to a single model. I

Local Ai

Framing Migration News with LLMs: Structured CoT as a Support for Human Interpretation

arXiv:2606.03761v1 Announce Type: new Abstract: Frame analysis of migration news is a socially consequential task: media scholars and researchers who study how migration is narrated need tools that ar

local-aiarxiv-cs-cl

From Prompt to Service: An SLM-Based Agent Orchestration Gateway for AI-Driven Virtual Worlds

arXiv:2606.03557v1 Announce Type: new Abstract: As generative AI capabilities expand, AI-driven virtual worlds face a growing architectural challenge. Users interact through in-world interfaces in mul

GeoDrive-Bench: Benchmarking Region-Specific Multimodal Reasoning in Autonomous Driving

arXiv:2606.02774v1 Announce Type: new Abstract: Vision-language models (VLMs) for autonomous driving have shown promising performance, but their ability to handle region-specific traffic rules remains

PSViT: A Methodology for Structurally Pruning Spiking Vision Transformers

arXiv:2606.03257v1 Announce Type: cross Abstract: Spiking Vision Transformer (SViT) models are promising low-power ViT models for solving vision-based tasks with state-of-the-art performance. However,

researcharxiv-cs-ai

TTT-VLA: Test-Time Latent Prompt Optimization for Vision-Language-Action Models

arXiv:2606.03127v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models trained on large-scale data have made remarkable progress, but they remain vulnerable to distribution shifts at depl

safetyarxiv-cs-ro

A Lightweight Hybrid MLP-Based Framework for Real-Time Phishing URL Detection Using Structural URL Features

arXiv:2606.00889v1 Announce Type: cross Abstract: Phishing attacks remain a major cybersecurity threat, exploiting deceptive URLs to steal sensitive user information. Traditional blacklist and rule-ba

A Practical Upper Bound on Selection Bias Effects in Medical Prediction Models

arXiv:2606.00563v1 Announce Type: cross Abstract: Selection bias is a common and often unavoidable aspect of real-world data that challenges the generalizability of machine learning models. When model

Agricultural Landscape Understanding At Country-Scale

arXiv:2411.05359v2 Announce Type: replace-cross Abstract: Comprehensive agricultural landscape understanding is critical for addressing global challenges in food security, climate change, and resource

Auditing Near-Optimal Policies Can Be Exponentially Hard: Conditional Query Lower Bounds via Occupancy Rashomon Capacity

arXiv:2606.00414v1 Announce Type: new Abstract: When many reinforcement-learning policies achieve near-optimal return, a post-hoc auditor may have to distinguish among many behaviorally distinct but r

Benchmarking Local LLMs for Natural-Language-to-SQL Querying in Biopharmaceutical Manufacturing: An Empirical Benchmark on Consumer-Grade Hardware

model-releasesarxiv-cs-cl

arXiv:2606.01338v1 Announce Type: new Abstract: Biopharmaceutical manufacturing organizations operate under regulatory frameworks such as FDA guidance, EU Good Manufacturing Practice (GMP), and the EU

Contrastive meta-domain adaptation for robust skin lesion classification across clinical and acquisition conditions

arXiv:2602.19857v2 Announce Type: replace Abstract: Deep learning models for dermatological image analysis remain sensitive to acquisition variability and domain-specific visual characteristics, leadi

researcharxiv-cs-cv

Hardware

CRAFT: Fine-Grained Cost-Aware Expert Replication For Efficient Mixture-of-Experts Serving

arXiv:2603.28768v2 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) has recently emerged as the mainstream architecture for efficiently scaling large language models while maintaining n

hardwarearxiv-cs-lg

Digital-to-Physical Transfer of Adversarial Patches for Aerial Vehicle Detection

arXiv:2606.00159v1 Announce Type: cross Abstract: Deep neural network (DNN)-based object detectors are widely used for analyzing aerial and satellite imagery in applications such as environmental moni

applicationsarxiv-cs-ai

Efficient LLM Moderation with Multi-Layer Latent Prototypes

arXiv:2502.16174v4 Announce Type: replace-cross Abstract: Although modern LLMs are aligned with human values during post-training, robust moderation remains essential to prevent harmful outputs at dep

Exploiting In-Sensor Computing for Energy-Efficient Earth Observation

arXiv:2606.01271v1 Announce Type: new Abstract: The rapid growth of the satellite industry has driven a significant increase in geospatial data acquisition, highlighting a critical bottleneck: the sev

researcharxiv-cs-cv

Interpretable Policy Distillation for Power Grid Topology Control

arXiv:2606.00561v1 Announce Type: cross Abstract: Deep reinforcement learning (RL) offers a promising route to real-time power grid operation, yet large neural policies are costly to evaluate, hard to

KISS: Keeping it Simple and Slotted when Learning to Communicate over Wireless

arXiv:2606.00266v1 Announce Type: cross Abstract: A long-standing challenge in distributed wireless systems is ensuring efficient and fair random channel access. Existing solutions often address speci

safetyarxiv-cs-lg

On the Evaluation of Spiking Neural Network Configurations for Network Intrusion Detection

arXiv:2606.01442v1 Announce Type: cross Abstract: Network intrusion detection is a core component of modern cybersecurity infrastructure, yet the deep learning models that dominate the field are compu

PACE: Phase-Aware Chunk Execution for Robot Policies with Action Chunking

arXiv:2606.00537v1 Announce Type: new Abstract: Recent vision-language-action and diffusion-based robot policies often use action chunking, where each policy query predicts a sequence of future action

safetyarxiv-cs-ro

Train, Test, Re-evaluate: Schedule-Sensitive Evaluation of Generative Data for Hand Detection

arXiv:2606.01896v1 Announce Type: cross Abstract: Generated (or synthetic) image data is increasingly used to augment or replace real training datasets when target imagery is scarce, expensive, or bia

Training-Free Imitation Learning with Closed-Form Diffusion Policies

arXiv:2606.01238v1 Announce Type: cross Abstract: While diffusion-based policies have impressive performance and expressivity, their long offline training slows down the data collection and policy dep

safetyarxiv-cs-lg

UME: A Unified Meta-Generalization Framework for Cross-Domain ETA

arXiv:2606.00979v1 Announce Type: new Abstract: Accurate Estimated Time of Arrival (ETA) prediction on checkout page is crucial in instant logistics for enhancing user satisfaction, optimizing dispatc

applicationsarxiv-cs-lg

Agents

Unsupervised Collaborative Domain Adaptation for Driving Scene Parsing

arXiv:2606.01818v1 Announce Type: new Abstract: Reliable driving scene parsing is a fundamental capability for autonomous vehicles operating in open and dynamic driving environments. However, adapting

agentsarxiv-cs-cv

Agents

VLAMotor: Test-Guided Enhancement of Vision-Language-Action Models via Agent-BasedData Synthesis

arXiv:2606.00053v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models follow a data-driven paradigm and are constrained by the coverage of training data, making them prone to failure on

agentsarxiv-cs-ro

Which Institutional Frameworks Do Chatbots Assume? Auditing Jurisdictional Defaults in Multilingual LLMs

arXiv:2606.00333v1 Announce Type: new Abstract: LLMs increasingly answer questions about taxes, labor protections, healthcare, education, pensions, and administrative procedures, where usefulness ofte

applicationsarxiv-cs-cl

Local Ai

Beyond Accuracy: Evaluating Efficiency, Robustness and Explainability in Deep Learning for Malaria Diagnosis

arXiv:2605.30734v1 Announce Type: cross Abstract: Malaria remains a leading cause of mortality in sub-Saharan Africa, where scarce diagnostic infrastructure makes timely, accurate diagnosis particular

local-aiarxiv-cs-cv

Hide-and-Seek in Trajectories: Discovering Failure Signals for VLA Runtime Monitoring

arXiv:2605.30834v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models enable robots to follow natural language instructions and generalize across diverse tasks, but they remain vulnera

applicationsarxiv-cs-ai

Knowledge Boundary Probing and Demand-Guided Intervention for LLM-Based Power System Code Generation

model-releasesarxiv-cs-cl

arXiv:2605.31478v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to automate power-system analysis, but many utilities and energy-research labs require on-premise s

Lightweight SAR Ship Detection via Contrastive Distillation

arXiv:2605.30380v1 Announce Type: new Abstract: Deep convolutional and transformer-based detectors achieve strong performance for SAR ship detection but are often computationally prohibitive for real-

researcharxiv-cs-cv

Local Ai

LocalSUG: City-Preference-Enhanced LLM for Query Suggestion in Local-Life Services

arXiv:2603.04946v2 Announce Type: replace Abstract: In local-life service platforms, query suggestion reduces user effort by generating candidate queries from input prefixes. Traditional multi-stage s

local-aiarxiv-cs-cl

QVGGT: Post-Training Quantized Visual Geometry Grounded Transformer

arXiv:2605.31124v1 Announce Type: new Abstract: Estimating 3D attributes directly from images has advanced rapidly with the Visual Geometry Grounded Transformer (VGGT), which predicts camera parameter

Hardware

Reducing the GPU Memory Bottleneck with Lossless Compression for ML -- Extended

arXiv:2605.30728v1 Announce Type: new Abstract: Machine learning (ML) training and inference often process data sets far exceeding GPU memory capacity, forcing them to rely on PCIe for on-demand tenso

hardwarearxiv-cs-lg

Smaller and Faster 3DGS via Post-Training Dictionary Learning

model-releasesarxiv-cs-lg

arXiv:2605.30396v1 Announce Type: cross Abstract: 3D Gaussian Splatting (3DGS) is a promising neural scene representation for real-time rendering, but trained models often suffer from large memory foo

The Challenges of Using Reinforcement Learning for Controlling Industrial Energy Systems

arXiv:2605.31044v1 Announce Type: new Abstract: Reinforcement learning has shown promising results for optimizing the control of industrial energy systems, yet most existing studies remain limited to

applicationsarxiv-cs-lg