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arXiv:2608.10618v1 Announce Type: new Abstract: Embodied artificial intelligence aims to develop agents that perceive, reason, and act through continuous interaction with the physical world. However,

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Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint

DGX agent

arXiv:2608.09998v1 Announce Type: new Abstract: Artificial Intelligence (AI) and Machine Learning (ML) have become powerful tools for supporting and automating complex human tasks. Despite their benef

researcharxiv-cs-ai

12 Aug 2026

TRACE-GS: On-Policy Trajectory Distillation with Privileged Geometric Conditioning for Sparse-View 3DGS Restoration

arXiv:2608.10286v1 Announce Type: new Abstract: We present TRACE-GS, an on-policy trajectory distillation framework that leverages privileged geometric conditioning at training time, thereby adapting

safetyarxiv-cs-cv

What We Know about Responsible AI Practices in Industry: A Half Decade of Empirical Research

arXiv:2608.10431v1 Announce Type: cross Abstract: Responsible AI (RAI) has become a central concern for technology companies, regulators, and the public. How industry practitioners interpret, implemen

When Agent Automation Becomes Profitable: Quantifying and Insuring Autonomous AI Risk through Trace-Economic Underwriting

arXiv:2606.16465v2 Announce Type: replace Abstract: AI agents can now take irreversible actions in operational systems, but agent-caused losses are still not clearly assigned, priced, or transferred.

When Repository Labels Are Not Image-Level Truth: A Supervision Auditing Framework for Chest Radiograph AI

arXiv:2608.10084v1 Announce Type: cross Abstract: Public chest X-ray repositories are widely used to train medical AI systems, yet their labels are typically extracted from radiology reports rather th

applicationsarxiv-cs-cv

When Your State Estimator Has Lost The Plot: Detecting Estimator Failures Via Spectral Analysis

arXiv:2608.10623v1 Announce Type: new Abstract: Reliable onboard state estimation is essential for safe robotic operation, yet unmodeled disturbances, such as sensor aliasing or out-of-distribution no

applicationsarxiv-cs-ro

A Communication-Efficient Digital Twin Framework for PSO-Based Swarm Navigation and Obstacle Avoidance

arXiv:2406.19930v4 Announce Type: replace Abstract: Swarm-based target localization in industrial environments faces two major challenges: navigating obstacle-rich spaces and managing intensive commun

agentsarxiv-cs-ro

A Minimal kappa--au Logic for Risk-Sensitive Abduction

arXiv:2608.08192v1 Announce Type: new Abstract: Standard approaches to abductive reasoning can retain multiple candidate explanations, but they do not generally combine explicit compositional cross-hy

researcharxiv-cs-ai

A Probabilistic Circuit-Induced Pseudo-Metric for Out-of-Distribution Detection

arXiv:2608.09117v1 Announce Type: new Abstract: Probabilistic Circuits (PCs) are tractable generative models whose internal nodes encode a hierarchy of probabilistic sum- maries over different variabl

researcharxiv-cs-lg

A Review of Vision-Based Vehicle Detection for UAV-Based Traffic Monitoring: Experimental Insights and Future Directions

arXiv:2608.07571v1 Announce Type: new Abstract: In Intelligent Transportation System (ITS), unmanned aerial vehicle (UAV)-based surveillance offers an innovative solution to traffic surveillance with

researcharxiv-cs-cv

Activation Probes Surface Code-Security Signals that the Model's Output Misses

arXiv:2608.09643v1 Announce Type: cross Abstract: AI coding agents now write a growing share of production code, and human security review does not scale at the rate code is generated. The agents in w

agentsarxiv-cs-lg

ActiveFly-Bench: Aligning Embodied Question Answering with Vision-Language-Action for Aerial Embodied Perception

arXiv:2607.10180v2 Announce Type: replace-cross Abstract: We introduce ActiveFly-Bench, the first benchmark to bridge cyberspace reasoning and physical-world interaction for UAV embodied perception. T

AdapterMoE: A Two-Stage Hard-Routing Mixture-of-Experts Architecture for Multi-Crop Disease Recognition with Calibrated Rejection and Incremental Learning

arXiv:2608.08808v1 Announce Type: new Abstract: Timely crop-disease identification is critical to food security. Multi-crop recognition suits Mixture-of-Experts (MoE), but conventional soft-routing Mo

researcharxiv-cs-cv

Adversarially Robust Few-Shot Anomaly Detection with Vision Foundation Models

arXiv:2510.13643v2 Announce Type: replace Abstract: Vision foundation models such as DINOv2 enable strong few-shot anomaly detection (FSAD) through simple non-parametric k-nearest-neighbor (k-NN) scor

researcharxiv-cs-cv

AeroDPO: Unleashing Lightweight UAV Navigation with High-Fidelity Perception and Automated Preference Optimization

arXiv:2608.07557v1 Announce Type: cross Abstract: Vision-Language Navigation for Unmanned Aerial Vehicles (UAV-VLN) requires rapid and reactive control in complex 3D environments. Recent minimalist en

Local Ai

Agentic AI-driven Immersive Simulation: A Knowledge-Aware Virtual Training Platform forHigh Dose Rate (HDR) Brachytherapy

arXiv:2608.08163v1 Announce Type: new Abstract: The convergence of the Metaverse and Large Language Model (LLM)-based AI agent is catalyzing a shift toward autonomous, immersive, and personalized peda

local-aiarxiv-cs-ai

AIVV: Neuro-Symbolic LLM Agent-Integrated Verification and Validation for Trustworthy Autonomous Systems

arXiv:2604.02478v2 Announce Type: replace Abstract: Deep learning models excel at detecting anomaly patterns in normal data. However, they do not provide a direct solution for anomaly classification a

AndroidReality: How Far Are Mobile Agents from the Real World?

arXiv:2608.07775v1 Announce Type: new Abstract: Mobile agents have achieved promising results on clean online benchmarks such as AndroidWorld, yet their performance often degrades sharply in real-worl

AnyCamVLA: Zero-Shot Camera Adaptation for Viewpoint Robust Vision-Language-Action Models

model-releasesarxiv-cs-ro

arXiv:2603.05868v2 Announce Type: replace Abstract: Despite remarkable progress in Vision-Language-Action models (VLAs) for robot manipulation, these large pre-trained models require fine-tuning to be

Beyond Pixels: Exploring DOM Downsampling for LLM-Based Web Agents

arXiv:2508.04412v3 Announce Type: replace Abstract: The advent of large language models (LLMs) has sparked an evolution of autonomous web browsing agents: given a web browsing task and serialised user

Compositional Threat Analysis of Latent Compromise in LLM Agent Systems: The Order 66 Scenario

arXiv:2608.08131v1 Announce Type: cross Abstract: In the fictional Order 66, catastrophe does not arise from a powerful command alone: a trusted population is preconditioned, a short directive activat

ConMem: Contribution-Aware Memory for Long-Horizon Manufacturing Inspection Logs

arXiv:2607.28126v2 Announce Type: replace Abstract: Long-horizon steel-equipment inspection requires reasoning over heterogeneous records accumulated across repeated inspection cycles. Existing retrie

applicationsarxiv-cs-ai

Contamination Means Overestimation? A Fine-Grained Empirical Study in Code Intelligence

arXiv:2506.02791v4 Announce Type: replace-cross Abstract: In recent years, code intelligence has gained increasing importance in the field of automated software engineering. Meanwhile, the widespread

ControlRadio: Prompt-Driven Controllable Diffusion for Cross-Modal Radio Map Generation

arXiv:2608.09357v1 Announce Type: new Abstract: Radio maps describe how wireless signals propagate across space and are essential for wireless communication, sensing, and network planning. However, co

applicationsarxiv-cs-cv

Conversation as Measurement in Clinical Encounters: Observable Phase Structure, Partially Observable Patient State

model-releasesarxiv-cs-cl

arXiv:2608.08868v1 Announce Type: new Abstract: Many modern AI systems analyze conversational traces to infer aspects of human interaction and state, implicitly assuming that such information is recov

CoRCi: Cross-Reconstruction of Coherent Interests Modeling in Cross-Domain Sequential Recommendation

arXiv:2608.09580v1 Announce Type: new Abstract: Cross-Domain Sequential Recommendation (CDSR) aims to alleviate data sparsity by transferring dynamic user interests across related domains. A key chall

Critic-Free Deep Reinforcement Learning for Maritime Coverage Path Planning on Irregular Hexagonal Grids

arXiv:2603.28385v2 Announce Type: replace-cross Abstract: Maritime surveillance missions, such as search and rescue and environmental monitoring, rely on the efficient allocation of sensing assets ove

CyberAGENTS: Structured Autonomy for Agentic Gamified Learning in Cybersecurity

arXiv:2608.07965v1 Announce Type: new Abstract: Gamification is especially effective in learning domains requiring active problem-solving and iterative skill-building, such as cybersecurity education.

Decoy Images Amplify Caption-Mediated Defenses Against Encoded Jailbreaks

arXiv:2608.01043v2 Announce Type: replace-cross Abstract: We report a counter-intuitive interaction between image inputs and existing black-box defenses on Vision--Language Models (VLMs): pairing an e

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection

arXiv:2608.08100v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) enables large language models to classify network flows and generate human-readable incident reports by retrievin

Designing for Ethical AI: HCI Feature Considerations to Improve Fairness and User Experience in AutoML use for Human Resources

arXiv:2608.07477v1 Announce Type: cross Abstract: This thesis examines the fairness of Automated Machine Learning (AutoML) tools in human resource hiring systems through the combined lenses of regulat

Diffuse the object, keep its label: curating detector training data from a few unlabeled photographs via VLM-built 3D vegetation scenes

model-releasesarxiv-cs-cv

arXiv:2608.09691v1 Announce Type: new Abstract: Labeled images of small objects hidden in vegetation are scarce, and detectors trained on them generalize poorly across sites. Rather than reusing label

DUET: A Diversity-Quality Duet of Distillation Experts for Two-Step Video Generation

arXiv:2608.09637v1 Announce Type: cross Abstract: Diffusion models have enabled high-quality video generation in recent years, but the high cost of iterative sampling hinders their practical deploymen

researcharxiv-cs-ai

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models

arXiv:2608.08138v1 Announce Type: new Abstract: Recent data protection laws have accelerated the adoption of Federated Learning (FL) for privacy-preserving decentralized training. Nevertheless, increa

safetyarxiv-cs-cv

Efficient identification of critical regions via Flow Matching-based Monte Carlo initialization

arXiv:2508.15318v5 Announce Type: replace-cross Abstract: Markov chain Monte Carlo (MCMC) is a standard tool for studying many-body systems, but its practical cost can become substantial, especially w

researcharxiv-cs-lg

EgoTrack3D: A Modular Framework for Egocentric 3D Object Tracking

arXiv:2608.08016v1 Announce Type: new Abstract: Understanding 3D scenes from egocentric video is fundamental for robotics and autonomous navigation, yet rapid viewpoint changes and partial occlusions

agentsarxiv-cs-cv

ElasticBack: Stealthy Conditional Backdoor in LLM-Agent Skills via Coupled Trigger-Rule Optimization

arXiv:2608.09577v1 Announce Type: new Abstract: Agent skills, bundles of instructions and resources that an LLM agent loads on demand, form an emerging supply chain where a single poisoned skill can p

Electric joins Databricks to bring WASM Postgres to AI agent sandboxes

Electric has partnered with Databricks to extend Databricks’ PostgreSQL capabilities from the lakehouse into edge environments. This collaboration allows a wide range of lightweight open‑source databa

agentsdatabricks

Tutorials

Epically Powerful: An open-source software and mechatronics infrastructure for wearable robotic systems

arXiv:2511.05033v2 Announce Type: replace Abstract: Epically Powerful is an open-source robotics infrastructure that streamlines the underlying framework of wearable robotic systems - managing communi

tutorialsarxiv-cs-ro

Ethical Framework for Responsible Foundational Models in Medical Imaging

arXiv:2406.11868v2 Announce Type: replace-cross Abstract: The emergence of foundational models represents a paradigm shift in medical imaging, offering extraordinary capabilities in disease detection,

Local Ai

Evidence-Calibrated Runtime Reconstruction for Agent Skills Across Heterogeneous Coding Agents

arXiv:2608.08793v1 Announce Type: new Abstract: Agent Skills package reusable instructions and assets for tool-using language-model agents. Progressive loading creates failure boundaries poorly repres

local-aiarxiv-cs-cl

Failure-Aware Long-Form Translation: Design and Implementation of a Recoverable LLM Translation System

arXiv:2608.09187v1 Announce Type: new Abstract: A long-form translation request can succeed at the API layer and still produce an unusable result. The output may be empty, truncated, filtered, dominat

researcharxiv-cs-cl

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning

arXiv:2608.09208v1 Announce Type: cross Abstract: Decentralized intelligence systems with heterogeneous devices and limited coordination increasingly rely on decentralized federated learning (DFL). Ho

From Relevance to Execution Utility: Reward-Aware Dynamic Execution Gating for Skill-Based LLM Agents

arXiv:2608.09168v1 Announce Type: new Abstract: Agent skills are increasingly used to equip large language model (LLM) agents with reusable procedural knowledge. Although recent work has substantially

Tutorials

From Trajectories to Evidence: Auditable Experimental Records for Industrial Research Agents

arXiv:2608.05235v1 Announce Type: cross Abstract: Research agents increasingly conduct multi-round machine-learning experiments in industrial recommendation settings and retain the resulting trajector

tutorialsarxiv-cs-ai

Full-Feature versus Limited-Input Machine Learning for Residential Energy Estimation: A Comparative Analysis of RECS and ResStock Under Realistic Input Constraints

arXiv:2608.09255v1 Announce Type: new Abstract: Residential energy estimates are often needed before detailed envelope characteristics, equipment efficiencies, infiltration, sensor, or billing data ar

researcharxiv-cs-lg

Goedel-Code-Prover: Hierarchical Proof Search for Open State-of-the-Art Code Verification

arXiv:2603.19329v3 Announce Type: replace-cross Abstract: Large language models (LLMs) can generate plausible code but offer limited guarantees of correctness. Formally verifying that implementations