Search: “deployment”

NVIDIA OmniDreams: Real-Time Generative World Model for Closed-Loop Autonomous Vehicle Simulation

arXiv:2606.03159v1 Announce Type: cross Abstract: As autonomous vehicle capabilities advance, the safe evaluation of driving policies in long-tail scenarios remains a critical bottleneck. In closed-lo

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Agents

OpenAgenet/OAN: Open Infrastructure for Trusted Agent Interconnection

DGX agent

arXiv:2606.03161v1 Announce Type: cross Abstract: OpenAgenet, abbreviated as OAN, is an open infrastructure project for trusted Agent interconnection. It addresses a problem that becomes visible when

agentsarxiv-cs-ai

3 Jun 2026

OpenAgenet/OAN: Technical Architecture for Trust-Governed Agent Identity and Discovery

arXiv:2606.03163v1 Announce Type: cross Abstract: This paper describes the technical architecture of OpenAgenet / OAN. OAN is a protocol-neutral trust layer for open Agent interconnection. It specifie

Patcher: Post-Hoc Patching of Backdoored Large Language Models

arXiv:2606.02995v1 Announce Type: cross Abstract: Large language models remain vulnerable to jailbreak backdoor attacks, where adversaries poison safety alignment data to embed hidden triggers that by

local-aiarxiv-cs-ai

PerchRL: Vision-Based Agile Perching on Inclined Platforms under Rapid and Irregular Motion

model-releasesarxiv-cs-lg

arXiv:2606.03441v1 Announce Type: cross Abstract: Autonomous vision-based perching of quadrotors on moving inclined platforms is critical for air-ground collaboration but remains challenging due to th

PHAF-Personalized Hand Avatars in a Flash

arXiv:2606.03420v1 Announce Type: new Abstract: We present PHAF-Personalized Hand Avatars in a Flash, a personalized photo-realistic hand avatar which provides high quality multi-view renders from jus

safetyarxiv-cs-cv

Qift: Shift-Friendly No-Zero W2 Post-Training Quantization for Rotated W2A4/KV4 LLM Inference

model-releasesarxiv-cs-lg

arXiv:2606.02823v1 Announce Type: new Abstract: Two-bit weight quantization is attractive for memory-efficient LLM inference, but the standard W2 level set {-2,-1,0,+1} often collapses under aggressiv

Quantifying Faithful Confidence Expression in Large Reasoning Models

arXiv:2606.03969v1 Announce Type: cross Abstract: Reliable uncertainty communication is critical to the trustworthiness of LLMs, yet faithful calibration (FC)--the alignment between models' intrinsic

See, Infer, Intervene: Proactive World Modeling for Goal-Oriented Social Intelligence

model-releasesarxiv-cs-cl

arXiv:2606.03371v1 Announce Type: new Abstract: Multimodal retail agents should not only recognize what a customer is doing, but also decide whether and how to assist before an explicit request is mad

Self-Refining Agentic Reinforcement Learning for Vision-Conditioned UAV Navigation

arXiv:2606.03963v1 Announce Type: cross Abstract: Deep reinforcement learning has shown strong potential for enabling autonomous robots to learn complex navigational tasks. However, its practical use

SimuScene: Simulation-Ready Compositional 3D Scene Reconstruction from a Single Image

arXiv:2606.03994v1 Announce Type: new Abstract: Reconstructing interactive, simulation-ready 3D scenes from a single image is a critical bottleneck for robotic manipulation. While recent single-image

safetyarxiv-cs-cv

Small RL Controller, Large Language Model: RL-Guided Adaptive Sampling for Test-Time Scaling

arXiv:2606.03102v1 Announce Type: new Abstract: Test-time scaling improves the reasoning performance of large language models but incurs substantial cost in both total computation and latency. Existin

researcharxiv-cs-cl

Speech Emotion Recognition using Attention-based LSTM-Network with Residual Connection

arXiv:2606.03359v1 Announce Type: cross Abstract: Speech emotion recognition is an important component of modern human-computer interaction systems. However, many state-of-the-art approaches rely on l

researcharxiv-cs-cl

SplitAdapter: Load-Aware Humanoid Loco-Manipulation via Factorized Adaptation

arXiv:2606.03297v1 Announce Type: new Abstract: Humanoid loco-manipulation requires stable whole-body control under varying object masses and pickup/placement heights. This becomes particularly challe

safetyarxiv-cs-ro

Taiji: Pareto Optimal Policy Optimization with Semantics-IDs Trade-off for Industrial LLM-Enhanced Recommendation

arXiv:2606.03866v1 Announce Type: cross Abstract: Scaling recommender systems via large language models (LLMs) has become a prominent trend in the industry. However, aligning the LLM's semantic space

The Agent's First Day: Benchmarking Learning, Exploration, and Scheduling in the Workplace Scenarios

arXiv:2601.08173v2 Announce Type: replace Abstract: The rapid evolution of Multi-modal Large Language Models (MLLMs) has advanced workflow automation; however, existing research mainly targets perform

The Epi-LLM Framework: probing LLM behavioral priors through epidemiological agent-based models

arXiv:2606.02867v1 Announce Type: cross Abstract: Human behaviour during epidemics affects infectious disease dynamics, but quantifying this remains deeply challenging. Here we introduce the Epi-LLM f

Tiny Collaborative Inference for Occlusion-Robust Object Detection

arXiv:2606.02894v1 Announce Type: new Abstract: Small edge devices such as IoT surveillance nodes and search-and-rescue (SAR) platforms are increasingly expected to run computer vision locally. On ult

local-aiarxiv-cs-cv

TriEval: A Resource-Efficient Pipeline for LLM Bias, Toxicity, and Truthfulness Assessment

arXiv:2606.03036v1 Announce Type: new Abstract: LLMs have evolved from basic chatbots to the backbone of the AI ecosystem, now widely used in healthcare, schools, and government services. The domain-w

Whose Name Comes Up? II: Benchmarking and Intervention-Based Auditing of LLM-Based Scholar Recommendation

arXiv:2602.08873v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are now used for academic expert recommendation. Existing audits typically evaluate such recommendations in isola

Applications

WISE-HAR: A Generalizable Ensemble Deep Learning Framework for WiFi-Based Human Activity Recognition

arXiv:2606.02974v1 Announce Type: new Abstract: Human Activity Recognition (HAR) using WiFi signals has emerged as a transformative technology for smart homes, healthcare monitoring, security systems,

applicationsarxiv-cs-ai

World Models Meet Language Models: On the Complementarity of Concrete and Abstract Reasoning

arXiv:2606.03603v1 Announce Type: cross Abstract: World models and multimodal large language models (MLLMs) provide complementary capabilities for predicting future outcomes from static visual observa

safetyarxiv-cs-cl

Worth Remembering: Surprise-Gated Robot Episodic Memory

arXiv:2606.03787v1 Announce Type: new Abstract: Robots solving generalist tasks need to be able to ground instructions in their past experience, since humans may refer to notable past events when givi

researcharxiv-cs-ro

A Comparative Analysis of Machine Learning Algorithms for Multi-Task Prediction of the Parameters of the Pectin Hydrolysis--Extraction Process

model-releasesarxiv-cs-lg

arXiv:2606.00821v1 Announce Type: new Abstract: This study addresses the challenge of controlling a complex, multi-parameter technological process -- pectin hydrolysis--extraction -- using machine lea

A Finite-Calibration Regime Map for LLM Judge Panels

model-releasesarxiv-cs-cl

arXiv:2606.01034v1 Announce Type: new Abstract: We study when LLM judge panels should be calibrated with low-dimensional stackers versus joint output tables under finite human-label budgets. Low-dimen

Applications

A Foundation Model for Wearable Movement Data in Mental Health Research

arXiv:2411.15240v5 Announce Type: replace-cross Abstract: Wearable movement data is collected by nearly all commercially available smartwatches and is a valuable resource for mental health research, r

applicationsarxiv-cs-ai

A Lightweight Context-Driven Training-Free Network for Scene Text Segmentation and Recognition

arXiv:2503.15639v2 Announce Type: replace-cross Abstract: Modern scene text recognition systems often depend on large end-to-end architectures that require extensive training and are prohibitively exp

researcharxiv-cs-ai

A Methodological Framework for Explicit Control of the Speed-Accuracy Trade-off in Brain-Computer Interfaces

arXiv:2606.00106v1 Announce Type: cross Abstract: Brain-computer interfaces (BCIs) are limited by low signal-to-noise ratio in modalities such as electroencephalography, which requires multiple trials

A Novel Data Augmentation Strategy for Robust Deep Learning Classification of Biomedical Time-Series Data: Application to ECG and EEG Analysis

arXiv:2507.12645v1 Announce Type: cross Abstract: The increasing need for accurate and unified analysis of diverse biological signals, such as ECG and EEG, is paramount for comprehensive patient asses

A Structured Benchmark for Text-Guided Anomaly Detection: When Language Stops Conditioning the Decision

arXiv:2606.01992v1 Announce Type: cross Abstract: Industrial anomaly detection has historically been a unimodal task. Recent multimodal vision-language models have produced systems that admit textual

Accuracy, Stability, and Repeated-Run Reliability of Large Language Models on Deterministic Programming Tasks

arXiv:2606.00920v1 Announce Type: cross Abstract: Run-level pass rate overstates retry-free coverage by up to 17.8 percentage points -- and the gap is largest precisely for mid-performing systems. We

Adaptive data selection improves wearable prediction under low baseline performance

arXiv:2606.00141v1 Announce Type: cross Abstract: Adaptive sensing strategies that selectively sample data are increasingly used in wearable health systems to improve prediction performance under limi

researcharxiv-cs-ai

Adversarial Feeds Steer LLM Agent Decisions Against Their Defaults

arXiv:2606.00914v1 Announce Type: new Abstract: LLM agents increasingly act after consuming ranked external information streams such as social feeds, search results, retrieval contexts, and email queu

Adversarially Robust Control of Conditional Value-at-Risk via Rockafellar-Uryasev Conformal Inference

arXiv:2606.00320v1 Announce Type: new Abstract: We present an online, distribution-free framework for controlling the Conditional Value-at-Risk (CVaR), extending conformal tail risk control to non-sta

safetyarxiv-cs-lg

AFUN: Towards an Affordance Foundation Model for Functionality Understanding

arXiv:2606.02551v1 Announce Type: cross Abstract: Affordance understanding bridges visual perception and physical action, serving as an explainable interface for robot manipulation in open and unstruc

local-aiarxiv-cs-cv

AgentxGCore: Agentic AI for Next-Generation Mobile Core Network

arXiv:2606.00417v1 Announce Type: cross Abstract: To meet the stringent requirements of emerging applications and the increasingly complex network management and operation, the Next Generation Mobile

AI Sovereignty as National Learning Capacity: A Human-Centered Learning Mechanics Viewpoint on France, the United States, and China

arXiv:2606.00729v1 Announce Type: new Abstract: Artificial Intelligence is often discussed in France in terms of investment, compute capacity, regulation, employment, sovereignty, and education. These

APE: Agentic Prompt Enhancer for Image Generation and Editing

model-releasesarxiv-cs-cv

arXiv:2606.00204v1 Announce Type: new Abstract: Natural language has become a powerful interface for image generation and editing, yet text-guided visual systems remain highly sensitive to prompt form

Approximate Imitation Learning for Event-based Quadrotor Flight in Cluttered Environments

arXiv:2603.07578v2 Announce Type: replace Abstract: Event cameras offer high temporal resolution and low latency, making them ideal sensors for high-speed robotic applications where conventional camer

safetyarxiv-cs-ro

ArrythML: An Autoencoder-Based TinyML Approach for On-Device Arrhythmia Detection on Resource-Constrained Embedded Systems

arXiv:2606.02256v1 Announce Type: new Abstract: Our work presents a method for ECG segmentation and arrhythmia detection using Tiny Machine Learning (TinyML) models for real-time, on-device inference

local-aiarxiv-cs-lg

Authenticity Debt and the Synthetic Content Threat Landscape: A Layered Framework for Trust, Provenance, and IP Governance in the Generative AI Era

arXiv:2606.00621v1 Announce Type: cross Abstract: Generative artificial intelligence has fundamentally changed how content is now produced. It has enabled how high-fidelity text, images, audio, and vi

Automatically Differentiable Nonlinear Tensor Networks (ADNTNs) for Exponential Compression of Deep Neural Networks

arXiv:2606.00130v1 Announce Type: cross Abstract: We study Automatically Differentiable Nonlinear Tensor Networks (ADNTNs), a family of structured weight generators whose compact core tensors are trai

researcharxiv-cs-ai

AXIOM: A Trust-First Neuro-Symbolic Execution Architecture for Verifiable Mathematical Reasoning

arXiv:2606.00671v1 Announce Type: new Abstract: We present AXIOM, a trust-first neuro-symbolic execution architecture for natural-language mathematical reasoning. In AXIOM, the language model function

Belief Consistency Between Foundation-Model Evidence and Geometric Perception in Persistent Robotic Maps

arXiv:2606.00318v1 Announce Type: cross Abstract: Persistent maps used by autonomous robots increasingly fuse a geometric perception stack whose assertions are well-characterized with a foundation-mod

agentsarxiv-cs-cv

BEVIO: Efficient Bird's-Eye-View based Sparse-Update Visual-Inertial Odometry for Lunar Day-Night Navigation

arXiv:2606.00709v1 Announce Type: new Abstract: Visual-Inertial Odometry (VIO) provides smooth, high-rate state estimates and has been widely used for robotic navigation in both terrestrial and planet

researcharxiv-cs-ro

Beyond End-to-End Video Models: An LLM-Based Multi-Agent System for Educational Video Generation

arXiv:2602.11790v2 Announce Type: replace Abstract: Although recent end-to-end video generation models demonstrate impressive performance in visually oriented content creation, they remain limited in

Beyond Pure Sampling: Hybrid Optimization Mechanisms for Non-Convex Model Predictive Control

arXiv:2606.00737v1 Announce Type: new Abstract: This paper investigates the optimization mechanisms of non-convex Model Predictive Control (MPC) using the Maximum Entropy Differential Dynamic Programm

local-aiarxiv-cs-ro

Hardware

BudgetDraft: Acceptance-Aware Multi-View Training for Sparse-KV Speculative Decoding

arXiv:2606.00144v1 Announce Type: cross Abstract: Speculative decoding speeds up autoregressive decoding by using a drafter to propose multiple tokens that a verifier validates in parallel. In resourc

hardwarearxiv-cs-ai