Search: “deployment”

RADAR: Closed-Loop Robotic Data Generation via Semantic Planning and Autonomous Causal Environment Reset

arXiv:2603.11811v2 Announce Type: replace-cross Abstract: The acquisition of large-scale physical interaction data, a critical prerequisite for modern robot learning, is severely bottlenecked by the p

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Agents

Rethinking Penetration Testing for AI-Enabled Systems: From Resource Compromise to Behavioral Objective Violation

DGX agent

arXiv:2607.14006v1 Announce Type: cross Abstract: Penetration testing traditionally evaluates whether adversaries can exploit weaknesses in software, infrastructure, configurations, or operational con

agentsarxiv-cs-ai

16 Jul 2026

RF-Informed Graph Neural Networks for Accurate and Data-Efficient Circuit Performance Prediction

arXiv:2508.16403v3 Announce Type: replace Abstract: Accurately predicting the performance of active radio frequency (RF) circuits is essential for modern wireless systems but remains challenging due t

researcharxiv-cs-lg

RF Spectrogram Anomaly Detection with Quantum Kitchen Sinks: Architecture, Representation, and Hardware Validation

model-releasesarxiv-cs-lg

arXiv:2607.13897v1 Announce Type: new Abstract: The broadcast nature of wireless channels exposes radio-frequency (RF) networks to anomalous and malicious transmissions, making anomaly detection a fun

SAFETY SENTRY: Context-Aware Human Intervention via EXECUTE-ASK-REFUSE Routing

arXiv:2607.13594v1 Announce Type: new Abstract: LLM agents act on real-world environments through tool calls, and a single misjudged action can cause irreversible harm. The standard safeguard is a gua

Self-Improving AI Coding Agents Through Accumulated Behavioral Rules: A Closed-Loop Framework

arXiv:2607.13091v1 Announce Type: cross Abstract: LLM-based coding agents repeat the same classes of mistakes across sessions because they lack a mechanism to retain corrections from human review feed

Semantic Anchoring for Robotic Action Representations

arXiv:2607.13597v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models inherit rich semantic representations from pretrained Vision-Language Models, yet fine-tuning on limited robot dem

applicationsarxiv-cs-ai

Temperature Scaling Is Not Enough: Calibration Gaps Under Human Label Distributions

arXiv:2607.13423v1 Announce Type: new Abstract: Temperature scaling is the dominant post-hoc calibration method in modern deep learning. Its theoretical justification rests on an assumption that is ra

safetyarxiv-cs-lg

Towards end-to-end optimization in multimaterial 3D printing

arXiv:2607.13174v1 Announce Type: cross Abstract: Multimaterial 3D printing enables the fabrication of functionally graded components, but optimizing their spatial material distribution alongside stru

applicationsarxiv-cs-ro

UniPhysGen: Unified Physical Grounding for Simulation-Ready 3D Assets

model-releasesarxiv-cs-cv

arXiv:2607.13586v1 Announce Type: new Abstract: Physically grounded 3D assets are increasingly important for embodied AI and robotic simulation. However, most existing 3D assets lack unified physical

Tutorials

Unlocking Latent Dimensions: Exploring Representations of Large-Scale X-ray Scattering Data using Variational Autoencoders

arXiv:2606.14999v2 Announce Type: replace Abstract: Scientific user facilities generate X-ray scattering data faster than traditional workflows can process them. We address this challenge across two s

tutorialsarxiv-cs-lg

UTS at ELOQUENT 2026 Voight-Kampff: structural shifts in AI writing bypass state-of-the-art detectors

arXiv:2607.13565v1 Announce Type: cross Abstract: We investigate which language model evasion attacks survive state-of-the-art adversarial fine-tuning, developing strategies that sweep the top 5 posit

researcharxiv-cs-ai

Worlds in One Demo: A Synthetic Data Engine for Learning Open-World Mobile Manipulation

arXiv:2607.13154v1 Announce Type: new Abstract: Learning open-world mobile manipulation policies requires vast data to achieve spatial generalization, long-horizon robustness, and scene generalization

applicationsarxiv-cs-ro

Local Ai

A Multi-Agent System for Autonomous, Fine-Tuning-Free Clinical Symptom Detection: Development and Validation Study

arXiv:2607.12886v1 Announce Type: new Abstract: Clinical notes contain many of the signs and symptoms that bring patients to care, yet this information rarely reaches structured fields. Existing extra

local-aiarxiv-cs-ai

A Replicate-and-Quantize Strategy for Plug-and-Play Load Balancing of Sparse Mixture-of-Experts LLMs

arXiv:2602.19938v2 Announce Type: replace Abstract: Sparse Mixture-of-Experts (SMoE) architectures are increasingly used to scale large language models efficiently, delivering strong accuracy under fi

researcharxiv-cs-lg

Adaptive Cross-Modal Fusion with Sparse Attention for Pedestrian Crossing Intention Prediction

model-releasesarxiv-cs-cv

arXiv:2607.12293v1 Announce Type: new Abstract: Predicting pedestrian crossing intention is a safety-critical task for autonomous driving, yet existing approaches often rely on single-modal inputs or

Agentic Service-Oriented Computing: A Manifesto for the Next Frontier of Service-Oriented Computing

arXiv:2607.12619v1 Announce Type: new Abstract: The rapid emergence of LLM-powered autonomous and semi-autonomous agents is reshaping software systems from static, request-response components into goa

Amplitude-Only FFN Intervention for Tool-Structured LLM Inference Method: Gated Evaluation Protocol, and Cross-Model Empirical Results

arXiv:2607.11183v2 Announce Type: replace Abstract: Large language models increasingly operate as tool-using agents, where small format, argument, or function-call errors can invalidate otherwise plau

agentsarxiv-cs-cl

Tutorials

Anatomy-Privileged Distillation with Token Routing for MRI-Based Prediction of Perineural Invasion

arXiv:2607.11987v1 Announce Type: new Abstract: Perineural invasion (PNI) is associated with poor postoperative outcomes in intrahepatic cholangiocarcinoma, but it is confirmed by surgical pathology.

tutorialsarxiv-cs-cv

Local Ai

Automated Tensor Scheduling for Hybrid CPU-GPU LLM Inference on Consumer Devices

arXiv:2607.10183v2 Announce Type: replace-cross Abstract: Running large language models on consumer devices such as laptops and desktops is challenging because model weights often exceed GPU memory ca

local-aiarxiv-cs-ai

Calibrated Selective Prediction Using Deep Ensembles for ROI-Based Thyroid Nodule Ultrasound Classification Under Dataset Shift: A Retrospective Evaluation

arXiv:2607.12075v1 Announce Type: cross Abstract: Background: Deep learning models can classify thyroid nodules on ultrasound, but reliable clinical decision support also requires calibrated probabili

Calibration-First Reward-Component Auditing for Reinforcement Learning Control in Smart Greenhouses

arXiv:2607.11959v1 Announce Type: new Abstract: Greenhouse reinforcement learning can test climate-control ideas at a speed and scale that is difficult to achieve with crop experiments alone. For smar

Contrastive-Augmented Flow Matching for Style-Content Disentanglement

arXiv:2607.12404v1 Announce Type: new Abstract: Learning representations that separate content and style is crucial for controllable generation and compositional generalization. However, diffusion and

applicationsarxiv-cs-cv

Critic Experience Bank: Self-Evolving Step-Level Confidence Estimation for LLM Agents

arXiv:2607.12397v1 Announce Type: new Abstract: LLM agents act in external environments where each action changes the state that later decisions condition on, and where a single wrong step can waste i

DeepTravel: An End-to-End Agentic Reinforcement Learning Framework for Autonomous Travel Planning Agents

arXiv:2509.21842v2 Announce Type: replace Abstract: Travel planning (TP) agent has recently worked as an emerging building block to interact with external tools/resources for travel itinerary generati

Directional Constraints for Efficient Exploration in Safe Reinforcement Learning

arXiv:2607.12784v1 Announce Type: cross Abstract: Reinforcement Learning has revolutionized the landscape of robotic research, allowing robust learning of complex robotic skills in simulation. However

safetyarxiv-cs-lg

Do AI Agents Know When a Task Is Simple? Toward Complexity-Aware Reasoning and Execution

arXiv:2607.13034v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly automate multi-step engineering and informatics workflows, yet they rarely ask how much effort a task act

Evidence-Grounded AI for Musculoskeletal Care

arXiv:2607.12527v1 Announce Type: new Abstract: Musculoskeletal diseases are among the leading causes of disability worldwide and create the greatest global need for rehabilitation. Because recovery,

Evidence-Grounded Verified Agentic Reasoning: A Path Toward Eliminating LLM Hallucination in Empirical Inference via Tool-Attested Kernel Proofs

arXiv:2607.12650v1 Announce Type: cross Abstract: Tool access alone does not make LLM empirical reasoning governable: accepted outputs need not descend from attested evidence, and accepted deductions

Exact and Calibrated Diffusion Reconstruction for Digital Breast Tomosynthesis

arXiv:2607.12937v1 Announce Type: cross Abstract: Limited-angle digital breast tomosynthesis (DBT) reconstructs a volume from a few low-dose projections over a narrow arc. At a representative nine-vie

researcharxiv-cs-cv

Exact and Certified Data Shapley for Weighted k-Nearest-Neighbor Regression and Soft-Label Prediction

arXiv:2607.11956v1 Announce Type: cross Abstract: Data Shapley is the standard principled answer to which training points are worth what, and its k-nearest-neighbor (KNN) specialization is the version

researcharxiv-cs-ai

ExToken: Structured Exploration for Efficient Vision-Language-Action Reinforcement Fine-tuning

arXiv:2607.12931v1 Announce Type: new Abstract: Reinforcement Learning (RL) has demonstrated significant potential for improving Vision-Language-Action (VLA) models on complex manipulation tasks. Howe

safetyarxiv-cs-ro

FairCoder: Probing LLM Bias in High-Stakes Decision Making via Coding Tasks

model-releasesarxiv-cs-cl

arXiv:2501.05396v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used in high-stakes decisions such as hiring and college admissions, making their social bias a critic

Fin-Analyst at FinMMEval 2026 Task 3: A Live Hybrid Trading Agent with LLM Specialists and Rule-Based Signals

arXiv:2607.12233v1 Announce Type: cross Abstract: Large language model (LLM) trading agents show promising performance in equity markets, yet remain narrowly focused on US equities with little evidenc

From Many to Meaningful: Feature-Guided Zero-Shot Chronic Kidney Disease Screening Using Large Language Models

model-releasesarxiv-cs-lg

arXiv:2607.12260v1 Announce Type: new Abstract: Early screening of chronic kidney disease (CKD) is essential for preventing irreversible progression; however, many machine learning (ML)-based screenin

From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data

arXiv:2607.12175v1 Announce Type: cross Abstract: X-ray tomography enables nondestructive characterization of material microstructures, while advances in micro-CT imaging have accelerated volumetric d

researcharxiv-cs-ai

GaitSpan: Growing Humanoid Locomotion from Walking to Running

arXiv:2607.12114v1 Announce Type: cross Abstract: A humanoid that can walk should not relearn locomotion from scratch to jog or run. Yet current approaches often obtain gait diversity by prescribing g

Hardware

Gradient-Free Topology Adaptation for Power Flow Surrogates via In-Context Whitening

arXiv:2607.12241v1 Announce Type: cross Abstract: Machine-learned surrogates for the AC power flow (ACPF) problem amortize the cost of repeated solves on a fixed network, but lose one to two orders of

hardwarearxiv-cs-lg

How to solve PostgreSQL multilingual full-text search limitations with AlloyDB AI

model-releasesgoogle-cloud-ai

AlloyDB powers enterprise-grade search for some of the largest organizations, providing robust hybrid search capabilities that combine text, vector, and keyword searches into a simple ranked SQL query

HSEmotion Team at the 11th ABAW Challenge: Multi-Task Learning and Ambivalence/Hesitancy Video Recognition

arXiv:2607.12774v1 Announce Type: cross Abstract: This article presents our results for the 11th Affective Behavior Analysis in-the-Wild (ABAW) competition. For multi-task learning with simultaneous p

Hy-Embodied-VLM-1.0: Efficient Physical-World Agents

model-releasesarxiv-cs-cv

arXiv:2607.12894v1 Announce Type: new Abstract: Building capable embodied agents requires not only multimodal perception and understanding, but also agentic capabilities for reasoning about actions, a

“I asked a few AI researchers whether they could name any other real-world software that scales so poorly. None of them could think of any. …

applicationsgary-marcus--x

“I asked a few AI researchers whether they could name any other real-world software that scales so poorly. None of them could think of any. Even outside the world of software, it’s hard to find a comp

Illuminant-Adaptive 3D Lookup Tables for Camera Color Correction

arXiv:2607.11681v2 Announce Type: replace Abstract: Color correction is a key component of camera image signal processing (ISP) pipelines, encompassing illuminant discounting and colorimetric mapping

researcharxiv-cs-cv

Imputation-free transformer learning enables robust Alzheimer's disease prediction and calibrated uncertainty quantification across heterogeneous clinical cohorts

arXiv:2607.11656v2 Announce Type: replace-cross Abstract: Accurate diagnostic classification and disease-severity prediction for Alzheimer's disease are hampered by the incompleteness and heterogeneit

safetyarxiv-cs-lg

In-Context Reinforcement Learning under Non-Stationarity: A Survey

arXiv:2607.11906v1 Announce Type: new Abstract: The development of decision-pretrained transformers, algorithm distillation, long-context meta-RL, and retrieval-augmented agents has renewed interest i

Internet of Agentic Things: Networked AI Agents for Closed-Loop IoT Orchestration

arXiv:2607.12662v1 Announce Type: new Abstract: The paper introduces the Internet of Agentic Things (IoAT), an architectural framework that integrates agentic AI, IoT, cyber-physical systems, Physical

Kernel PCA for Out-of-Distribution Detection: Non-Linear Kernel Selection and Approximation

arXiv:2505.15284v2 Announce Type: replace-cross Abstract: Out-of-Distribution (OoD) detection is vital for the reliability of deep neural networks, the key of which lies in effectively characterizing

applicationsarxiv-cs-cv

Lightweight Multi-Scale Anomaly Detection for Resource-Constrained Edge Devices

model-releasesarxiv-cs-lg

arXiv:2607.12599v1 Announce Type: new Abstract: Time-series anomaly detection is increasingly important in IoT systems, sensor networks, and edge monitoring applications, where models must operate und