Search: “applications”

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios

arXiv:2506.18682v3 Announce Type: replace-cross Abstract: Recent advances in autonomous driving (AD) have highlighted the potential of hyperspectral imaging (HSI) for enhanced environmental perception

hardwarearxiv-cs-ai

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Research

On the Pseudo-Mixing of Kac's Walk

DGX agent

arXiv:2608.17374v1 Announce Type: cross Abstract: Motivated by a conjecture of Vaikuntanathan and Zamir, we study the pseudo-mixing of Kac's walk on SO(n): whether short trajectories are indistinguish

researcharxiv-cs-lg

19 Aug 2026

Optimize Your Sampling: Tuned Diffusion Sampling with Bayesian Optimization

arXiv:2608.18040v1 Announce Type: cross Abstract: Sampling from a diffusion model typically requires many forward passes through a large neural network, making generation computationally expensive. Wh

Picard Proximal Monte Carlo for Parallel Bayesian Imaging with Score-Based Generative Priors

arXiv:2608.17666v1 Announce Type: new Abstract: Bayesian imaging inverse problems often require sampling from high-dimensional posterior distributions. While recent score-based and diffusion models pr

hardwarearxiv-cs-lg

Picture the Epsilon: Pursuing Identity-Level Privacy Guarantees for Images

arXiv:2608.17147v1 Announce Type: cross Abstract: Image-to-image face generators are widely used, and visual dissimilarity between their outputs and source images is sometimes treated as evidence of p

Policy Optimization and Statistical Inference for Online Contextual Matrix Games

arXiv:2608.17173v1 Announce Type: cross Abstract: Online decision making often requires navigating a landscape shaped by both dynamic contexts and strategic interactions. In competitive pricing, for e

Local Ai

Predicting Male Domestic Violence Using Explainable Ensemble Learning and Exploratory Data Analysis

arXiv:2403.15594v4 Announce Type: replace-cross Abstract: Domestic violence is commonly viewed as a gendered issue that primarily affects women, which tends to leave male victims largely overlooked. T

local-aiarxiv-cs-lg

Runtime Governance for Agentic AI: Action-Boundary Control with Trusted Provenance and Fail-Closed Execution

arXiv:2608.16891v1 Announce Type: new Abstract: Agentic AI systems request tool actions that can modify files, send messages, launch jobs, or change workflow state. This shifts the safety problem from

safetyarxiv-cs-ai

Scale Matters: Adaptive Granularity Selection for Cross-Species 3D Plant Organ Segmentation

arXiv:2608.17803v1 Announce Type: new Abstract: Recent 3D foundation models provide powerful feature representations for point cloud learning by controlling spatial granularity. However, relying on a

SIGMA: SHAP-Guided Implicit-Trajectory Generation for Metadata-Free LLM-Based AutoFE

arXiv:2608.17948v1 Announce Type: cross Abstract: Recent research has leveraged Large Language Models (LLMs) to enhance Automated Feature Engineering (AutoFE) through semantic descriptions and traject

SignalReasoner: Assessing the Upper Bound of 3B Models for Signal Mathematical Reasoning

arXiv:2608.17301v1 Announce Type: new Abstract: Post-training with supervised chain-of-thought fine-tuning and reinforcement learning from verifiable rewards has substantially improved the mathematica

Tight Bounds for Data-driven Multiple Hyper-parameter Tuning with Structured Loss Function

arXiv:2608.17343v1 Announce Type: new Abstract: Data-driven algorithm design frames hyperparameter tuning as a statistical learning problem, but establishing generalization guarantees remains challeng

Agents

tinyDSM: A Framework for Skill Modeling and Development for Resource-Constrained Millirobots

arXiv:2608.17596v1 Announce Type: cross Abstract: In this study, we investigate developmental mechanisms that enable small, resource-constrained systems such as cm-sized millirobots to autonomously ex

agentsarxiv-cs-ai

TSQueryBench: LLM-as-a-Judge for Time Series Explanations

arXiv:2604.02118v2 Announce Type: replace Abstract: Natural language explanations of time series data are increasingly produced by foundation models in high stakes domains, making factual correctness

Unsupervised Deep Generative Models for Anomaly Detection in Neuroimaging: A Systematic Scoping Review

arXiv:2510.14462v3 Announce Type: replace Abstract: Unsupervised anomaly detection (UAD) based on deep generative modelling has been increasingly explored for identifying pathological brain abnormalit

A Generative Deep Learning Workflow for Inverse Molecular Design of Fuels

arXiv:2504.12075v4 Announce Type: replace Abstract: In the present work, a generative deep learning framework combining a Co-optimized Variational Autoencoder (Co-VAE) with quantitative structure-prop

A Highly Efficient Diversity-based Input Selection for DNN Improvement Using VLMs

arXiv:2601.08024v2 Announce Type: replace Abstract: Maintaining or improving the performance of Deep Neural Networks (DNNs) through fine-tuning requires labeling newly collected inputs, a process that

A Human-Centred Approach to Benchmarking LLMs for Parenting Advice

arXiv:2608.14622v1 Announce Type: new Abstract: People are increasingly using large language models (LLMs) to seek advice, including for parenting. Parenting is a critical and socially sensitive domai

researcharxiv-cs-ai

A survey of AI-generated voices and their detection

arXiv:2608.15411v1 Announce Type: new Abstract: The ability of artificial intelligence (AI) models to generate highly realistic human voices has advanced rapidly. These technologies power accessibilit

A Two-Stage Learning PINN Approach for Solving the Inverse Problem of the 1D Porous Medium Equation

arXiv:2608.16475v1 Announce Type: cross Abstract: The Porous Medium Equation (PME), given by u_t = Delta(u^m) for m > 1, is a degenerate nonlinear parabolic partial differential equation that arises i

AeroCopilotBench: A Two-Tier Benchmark for Evaluating LLM Agents as Aviation Copilots in an Interactive Virtual Cockpit Environment

arXiv:2608.16349v1 Announce Type: new Abstract: Large language model (LLM) agents may assist flight crews with complex decisions and task execution, but existing aviation evaluations centered on stati

AeroGround: A Comprehensive Benchmark for Aerial-Ground Collaborative Reasoning

model-releasesarxiv-cs-cv

arXiv:2608.14721v1 Announce Type: new Abstract: Vision-language models (VLMs) have been widely employed in understanding and reasoning tasks for unmanned aerial vehicles (UAVs). Existing UAV benchmark

Agents

ALKEMIE Agent: an autonomous platform for computational materials design

arXiv:2608.15776v1 Announce Type: cross Abstract: Despite the powerful multi-scale modeling methods and high-throughput infrastructures established in the materials community, real material computatio

agentsarxiv-cs-ai

Agents

An Agentic Framework Using Rules and LLMs for Embedding and Annotating Descriptive Document Layouts: A Plant Science Use Case

arXiv:2608.14587v1 Announce Type: new Abstract: Background: Recent advances in information retrieval (IR) leverage both dense and sparse representations, large language models (LLMs), and specialized

agentsarxiv-cs-ai

An automatic-differentiation framework for time-lapse electrical resistivity tomography inversion of hydrologic dynamics

arXiv:2608.14661v1 Announce Type: new Abstract: Time-lapse electrical resistivity tomography (TL-ERT) provides spatially distributed information on subsurface hydrologic changes. However, inversion of

hardwarearxiv-cs-lg

AnchorScore: A CLIP-Based Diagnostic of MLLM Annotation Difficulty

arXiv:2608.16690v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are widely used for automated annotation, yet their per-class accuracy varies widely (e.g., 12%-98% across the

Audio-Visual Segmentation via Depth-Guided Collaborative Modeling

arXiv:2608.16285v1 Announce Type: cross Abstract: Audio-Visual Segmentation (AVS) is a fundamental task in multimodal perception that performs pixel-level segmentation of sounding objects in videos by

safetyarxiv-cs-ai

BASeg: Boundary-Aware Remote Sensing Segmentation with Structural Penalties

model-releasesarxiv-cs-cv

arXiv:2608.15683v1 Announce Type: new Abstract: Semantic segmentation is a core computer vision task in the remote sensing field, accelerating advancements in ur- ban development, agriculture, ecology

Beyond Boundary Noise: Aggregated Aleatoric Uncertainty Fails to Capture Presence Ambiguity in 3D Lung Nodule Segmentation

arXiv:2608.14766v1 Announce Type: new Abstract: Uncertainty estimation is critical for the safe clinical deployment of deep learning in medical image segmentation, with aleatoric uncertainty theoretic

safetyarxiv-cs-cv

Local Ai

Beyond Single Object: Learning 3D Relations with Large Language Models

arXiv:2608.15710v1 Announce Type: cross Abstract: We address a fundamental gap in 3D-LLMs: existing models focus on single-object/scene description, struggling with detailed, inter-object comparison.

local-aiarxiv-cs-ai

Beyond Tokens: A Survey on Decoding Methods for Large Language and Vision-Language Models

arXiv:2608.14797v1 Announce Type: new Abstract: Large language models (LLMs) and large vision-language models (LVLMs) have demonstrated impressive generative capabilities, yet ensuring their outputs a

researcharxiv-cs-cl

Breaking and Defending LLM-Powered Social Media Bot Detection Systems

arXiv:2608.15893v1 Announce Type: new Abstract: The rise of social media bots poses a persistent threat, enabling misinformation, opinion manipulation, and the erosion of trust in online platforms. To

Co-design of Neural and Muscle Network based on Embodied Perceptron Representation

arXiv:2608.16555v1 Announce Type: new Abstract: Recent advances in AI technologies have enabled the advanced design of complex control policies. In contrast, focusing on the body, many robots still em

safetyarxiv-cs-ro

CoM^3eT: A foundation model for medical image analysis through federated, multidimensional context integration

arXiv:2608.16268v1 Announce Type: new Abstract: Medical foundation models improve generalization when training AI models with limited labeled data, but remain confined to a single specialty, such as p

hardwarearxiv-cs-cv

Concept-based explanation of gene expression prediction from H&E images

arXiv:2608.16669v1 Announce Type: new Abstract: Recent advances in pathology foundation models have enabled accurate prediction of spatial transcriptomics (ST) from routine H&E images. However, existi

Constraint-Aware Synthetic Tabular Data Generation via Inter-Column Constraint Discovery with LLM Agents

arXiv:2608.15109v1 Announce Type: new Abstract: Generating structurally valid synthetic tabular data remains difficult: outputs with high statistical fidelity and downstream utility can still violate

researcharxiv-cs-ai

Convolution Smoothed Quantile Regression for XGBoost

arXiv:2608.15290v1 Announce Type: cross Abstract: The increasing availability of large and complex datasets across many scientific disciplines has led to widespread adoption of machine learning (ML) f

Coverage-Maximizing Multinomial Subset Routing under Operational Constraints

arXiv:2608.16375v1 Announce Type: cross Abstract: We introduce Multinomial Subset Routing (MSR), a new online routing framework over K experts in which the learner keeps a multinomial routing policy i

safetyarxiv-cs-ai

CSMoE: An Efficient Remote Sensing Foundation Model with Soft Mixture-of-Experts

arXiv:2509.14104v2 Announce Type: replace Abstract: Self-supervised learning (SSL) through masked autoencoders (MAEs) has recently attracted great attention for remote sensing (RS) foundation model (F

Decision-Driven Regularization: A Blended Model for Learning and Optimization

arXiv:2608.15124v1 Announce Type: new Abstract: In contextual optimization, the decision-maker seeks optimal decisions to minimize a cost function, that varies based on observed features. This context

Local Ai

Demo: Real-time Generative Multicasting with On-Device Intent-aware Semantic Decomposition

arXiv:2608.14600v1 Announce Type: cross Abstract: We present a demonstration for generative multicasting with on-device, intent-aware semantic decomposition. At the transmitter, DNN-based segmentation

local-aiarxiv-cs-lg

Deploying Frontier Agentic Technology in MOOSEnger, a Multiphysics-Capable AI Assistant

arXiv:2608.15881v1 Announce Type: new Abstract: The Multiphysics Object-Oriented Simulation Environment (MOOSE) is an open-source finite-element framework for building multiphysics simulation applicat

Detector-Augmented SAMURAI for Long-Duration Drone Tracking

arXiv:2601.04798v2 Announce Type: replace Abstract: Robust long-term tracking of drone is a critical requirement for modern surveillance systems, given their increasing threat potential. While detecto

Tutorials

Domain Agnostic Text Redaction from Natural Language Rules using Instruction Tuning

arXiv:2608.14693v1 Announce Type: cross Abstract: With the increasing digitization of personal and corporate communication, the automatic sanitization of textual data has become a crucial component of

tutorialsarxiv-cs-ai

DYNASHIELD: A Black-Box Moving Target Defense for LLMs via Dynamic Decoding Customization

arXiv:2412.07672v2 Announce Type: replace-cross Abstract: Large language models (LLMs) remain vulnerable to jailbreak attacks in which adversarial prompts induce harmful outputs. Existing defenses oft

safetyarxiv-cs-cl

Explainability Boosted Anomaly Detection Framework for O-RAN based NextG Networks

arXiv:2608.14826v1 Announce Type: cross Abstract: The wireless networks have historically faced significant security vulnerabilities, necessitating advanced anomaly detection mechanisms, especially as

FETERS: Few-Shot Early Time-Series Classification via Effective Ratio Selection

arXiv:2608.16385v1 Announce Type: new Abstract: Early time-series classification (ETSC) aims to make accurate predictions from partially observed time series as early as possible. Although various sto

FLOPs vs Real Work: The Importance of Replication in AI Efficiency Assessment

arXiv:2608.14550v1 Announce Type: new Abstract: AI efficiency has recently taken the spotlight in both academy and industry due to massive model scales, high energy demands, and environmental costs. W

researcharxiv-cs-ai