Search: “applications”

Context-Aware Deep Learning for Defect Classification in Atomic-Resolution STEM

arXiv:2606.09419v1 Announce Type: cross Abstract: Artificial intelligence is rapidly advancing materials characterization, yet most applications in electron microscopy rely solely on image contrast, o

agentsarxiv-cs-ai

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Research

DiffoR: A Unified Continuous Generative Framework for Universal Ordinal Regression

DGX agent

arXiv:2606.07599v1 Announce Type: cross Abstract: Ordinal Regression (OR) aims to predict target values with inherent order, underpinning critical applications across diverse domains, from recommender

researcharxiv-cs-ai

9 Jun 2026

Discovering heuristics in a complex SAT solver with large language models

arXiv:2507.22876v2 Announce Type: replace Abstract: The Satisfiability problem (SAT) is fundamental in computational complexity theory and has a wide range of industrial applications. Optimizing moder

Dual Quaternion-Based Unscented Kalman Filter with Visual Inertial Odometry for Navigation in GPS-Denied Environments

model-releasesarxiv-cs-ro

arXiv:2606.09292v1 Announce Type: new Abstract: Reliable navigation in GPS-denied environments remains a fundamental challenge in robotics, aerospace, and autonomous vehicle applications. This paper p

EditSSC: Toward Editable Semantic Occupancy Scenes with Unconditional Diffusion Models

arXiv:2606.09273v1 Announce Type: new Abstract: 3D semantic scene generation is crucial for autonomous driving applications, yet most methods rely on complex 3D-specific architectures such as triplane

agentsarxiv-cs-cv

Efficient Onboard Vision-Language Inference in UAV-Enabled Low-Altitude Economy Networks via LLM-Enhanced Optimization

arXiv:2510.10028v2 Announce Type: replace-cross Abstract: The rapid advancement of Low-Altitude Economy Networks (LAENets) has enabled a variety of applications, including aerial surveillance, environ

Entropic Optimal Transport Eigenmaps for Nonlinear Alignment and Joint Embedding of High-Dimensional Datasets

arXiv:2407.01718v2 Announce Type: replace-cross Abstract: Embedding high-dimensional data into a low-dimensional space is an indispensable component of data analysis. In numerous applications, it is n

FADTI: Fourier and Attention Driven Diffusion for Multivariate Time Series Imputation

arXiv:2512.15116v2 Announce Type: replace-cross Abstract: Multivariate time series imputation is fundamental in applications such as healthcare, traffic forecasting, and biological modeling, where sen

safetyarxiv-cs-ai

Local Ai

Federated Large Language Models: Current Progress and Future Directions

arXiv:2409.15723v3 Announce Type: replace Abstract: Large Language Models have achieved impressive performance across diverse applications, yet their training typically depends on centralized data col

local-aiarxiv-cs-lg

FlowLet: Conditional 3D Brain MRI Synthesis using Wavelet Flow Matching

arXiv:2601.05212v2 Announce Type: replace Abstract: Brain Magnetic Resonance Imaging (MRI) plays a central role in studying neurological development, aging, and diseases. One key application is Brain

safetyarxiv-cs-cv

Graph-GRPO: Training Graph Flow Models with Reinforcement Learning

arXiv:2603.10395v2 Announce Type: replace Abstract: Graph generation is a fundamental task with broad applications, such as drug discovery. Recently, discrete flow matching-based graph generation, aka

researcharxiv-cs-lg

Harnessing Streaming Video in the Wild

model-releasesarxiv-cs-cv

arXiv:2606.08615v1 Announce Type: new Abstract: Vision-Language Models (VLMs) are increasingly required to process unbounded video streams in applications such as video-call assistants, live commentar

Hyperspectral Smoke Segmentation via Mixture of Prototypes

arXiv:2602.10858v2 Announce Type: replace Abstract: Smoke segmentation is critical for wildfire management and industrial safety applications. Traditional visible-light-based methods face limitations

safetyarxiv-cs-cv

Joint Structural Pruning and Mixed-Precision Quantization for LLM Compression

arXiv:2606.07819v1 Announce Type: new Abstract: Recently, the efficiency of Large Language Models (LLMs) deployment has become a critical concern in practical applications. While post-training quantiz

Language-based Trial and Error Falls Behind in the Era of Experience

arXiv:2601.21754v3 Announce Type: replace Abstract: While Large Language Models (LLMs) excel in language-based agentic tasks, their applicability to unseen, nonlinguistic environments (e.g., symbolic

Learning Predictive Control with Deep Koopman Operators for Autonomous Vehicle Motion Planning

model-releasesarxiv-cs-ro

arXiv:2606.08136v1 Announce Type: new Abstract: Model Predictive Control (MPC) is widely used for autonomous-vehicle (AV) motion planning, but its real-time applicability is often limited by the need

More Yap Less Meaning: Uncovering Self-Improvement Behavior in SLMs

arXiv:2606.08471v1 Announce Type: cross Abstract: Recently, language models have made rapid progress across various domains and applications. However, their capability for self-improvement, i.e., whet

MS-COOT: Comparing Morse-Smale Complexes with Co-Optimal Transport

arXiv:2606.08258v1 Announce Type: cross Abstract: Understanding and comparing structures in scalar fields is a central challenge in scientific visualization, with applications ranging from feature ana

NGram-MoSE: Efficient Remote Sensing Super-Resolution via N-Gram Context and Mixture-of-Experts

model-releasesarxiv-cs-cv

arXiv:2606.08535v1 Announce Type: new Abstract: Remote sensing applications for environmental monitoring and disaster management are frequently constrained by a spatial--temporal trade-off: imagery wi

Optimizing Energy-based Neural Network Training with Coherent Ising Machine

arXiv:2606.09117v1 Announce Type: cross Abstract: While Ising machines serve as advanced physical solvers for the Ising model,enabling applications in combinatorial optimization and neural network tra

Local Ai

PicoSAM3: Real-Time In-Sensor Region-of-Interest Segmentation

arXiv:2603.11917v2 Announce Type: replace Abstract: Real-time, on-device segmentation is critical for latency-sensitive and privacy-aware applications such as smart glasses and Internet-of-Things devi

local-aiarxiv-cs-cv

PolyBuild: An End-to-End Method for Polygonal Building Contour Extraction from High-Resolution Remote Sensing Images

arXiv:2606.08920v1 Announce Type: cross Abstract: Extracting building polygon contours from high-resolution remote sensing images is a fundamental task for various mapping applications. However, the p

Prescriptive Scaling Reveals the Evolution of Language Model Capabilities

arXiv:2602.15327v2 Announce Type: replace-cross Abstract: Machine learning model performance improvements tend to arise from competition and application. For deployment, we consider prescriptive scali

QnRL: Quantum-Native Reinforcement Learning

arXiv:2606.08276v1 Announce Type: cross Abstract: Quantum reinforcement learning (QRL) is a promising approach to learn effective decision strategies across several applications with stochastic enviro

QueryWeaver: Reliable Multi-Tool Query Execution Planning via LLM-Based Graph Generation

arXiv:2606.08300v1 Announce Type: new Abstract: Many real-world queries over personal data span multiple applications and require structured planning, as individual tools expose only partial informati

agentsarxiv-cs-lg

Rank Intervals for Leaderboards: A Hierarchical Framework for Model Evaluation

arXiv:2606.08679v1 Announce Type: cross Abstract: Pretrained models are often evaluated on multi-task leaderboards to measure their applicability in diverse contexts. However, current methods for aggr

researcharxiv-cs-lg

SOMA: From Surface Observations to Muscle Anatomy

arXiv:2606.09246v1 Announce Type: new Abstract: With the growing demand for realistic virtual humans, parametric body models have become a cornerstone of modern medicine, sports, and entertainment app

Tutorials

SRT: Super-Resolution for Time Series via Disentangled Rectified Flow

arXiv:2606.07605v1 Announce Type: cross Abstract: Fine-grained time series data with high temporal resolution is critical for accurate analytics across a wide range of applications. However, the acqui

tutorialsarxiv-cs-ai

State Backdoor: Towards Stealthy Real-world Poisoning Attack on Vision-Language-Action Model in State Space

arXiv:2601.04266v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models are widely deployed in safety-critical embodied AI applications such as robotics. However, their complex m

Steer Where It Matters: Token-Level Visual-Sensitivity Steering for LVLMs Hallucination Mitigation

arXiv:2606.07647v1 Announce Type: new Abstract: Large vision language models (LVLMs) have made rapid advancements and are deployed across various applications, yet hallucinations remain a major challe

The Confidence Trap: Calibration Attacks for Graph Neural Networks

arXiv:2606.08467v1 Announce Type: cross Abstract: While confidence calibration is essential for trustworthy decision-making in safety-critical applications, the robustness of calibrated GNNs to advers

safetyarxiv-cs-ai

Local Ai

Trajectory Optimization in Single and Dual-UAV Bearing-Only Target Localization

arXiv:2606.09188v1 Announce Type: cross Abstract: Bearing-only target localization is a fundamental problem in optical measurement and finds extensive applications in unmanned aerial vehicle (UAV) tec

local-aiarxiv-cs-cv

Unification of Closed-Open Industrial Detection Scenarios: New Large-Scale Benchmarks,Challenges and Baselines

arXiv:2606.07953v1 Announce Type: new Abstract: Large-scale Visual-Language Models (LVLMs) have achieved remarkable success in natural visual tasks, yet their application to industrial defect detectio

Zero Touch Predictive Orchestration: Automating Time-Series Models for the Cloud-Edge Continuum

arXiv:2606.09787v1 Announce Type: new Abstract: The Cloud-Edge Continuum (CEC) enables latency-critical applications by distributing resources to the far edge, but its extreme volatility makes proacti

researcharxiv-cs-lg

ADAGE: Active Defenses Against GNN Extraction

model-releasesarxiv-cs-lg

arXiv:2503.00065v4 Announce Type: replace-cross Abstract: Graph Neural Networks (GNNs) achieve high performance in various real-world applications, such as drug discovery, traffic states prediction, a

Bias in Filter Feature Selection Evaluation: A Meta-Analysis of Datasets, Baselines, and Experimental Design Choices

arXiv:2606.07068v1 Announce Type: new Abstract: Background: Since 1990 many feature selection methods have been proposed across heterogeneous applications. To validate the usefulness of a new method,

COMPOSE: Hypergraph Cover Optimization for Multi-view 3D Human Pose Estimation

arXiv:2601.09698v2 Announce Type: replace Abstract: 3D human pose estimation from sparse multi-view camera rigs is an essential task for numerous applications, including action recognition, sports ana

CountsDiff: A Diffusion Model on the Natural Numbers for Generation and Imputation of Count-Based Data

arXiv:2604.03779v2 Announce Type: replace-cross Abstract: Diffusion models have excelled at generative tasks for both continuous and token-based domains, but their application to discrete ordinal data

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators

arXiv:2606.06515v1 Announce Type: cross Abstract: Transformer-based networks have emerged as prominent AI models with state-of-the-art performance, which potentially pave the way toward artificial gen

HORUS: A Mixed Reality Interface for Managing Teams of Mobile Robots

arXiv:2506.02622v2 Announce Type: replace Abstract: Mixed Reality (MR) interfaces have been extensively explored for controlling mobile robots, but there is limited research on their application to ma

researcharxiv-cs-ro

Image class translation: visual inspection of class-specific hypotheticals and classification based on translation distance

arXiv:2408.08973v3 Announce Type: replace Abstract: Purpose: A major barrier to the implementation of artificial intelligence for medical applications is automated CNNs' lack of explainability and hig

Hardware

LuMamba: Latent Unified Mamba for Electrode Topology-Invariant and Efficient EEG Modeling

arXiv:2603.19100v2 Announce Type: replace Abstract: Electroencephalography (EEG) enables non-invasive monitoring of brain activity across clinical and neurotechnology applications, yet building founda

hardwarearxiv-cs-ai

Model Context Protocols in Adaptive Transport Systems: A Survey

arXiv:2508.19239v2 Announce Type: replace Abstract: The rapid expansion of interconnected devices, autonomous systems, and AI applications has created severe fragmentation in adaptive transport system

agentsarxiv-cs-ai

PandaAI: A Practical Agent CQ2 for Neuro-symbolic Data Analysis And Integrated Decision-Making in Quantitative Finance

arXiv:2606.06823v1 Announce Type: cross Abstract: While deep learning has excelled in various domains, its application to sequential decision-making in finance remains challenging due to the low Signa

agentsarxiv-cs-ai

PolarQuant: Leveraging Polar Transformation for Efficient Key Cache Quantization and Decoding Acceleration

arXiv:2502.00527v2 Announce Type: replace-cross Abstract: The KV cache in large language models is a dominant factor in memory usage, limiting their broader applicability. Quantizing the cache to lowe

researcharxiv-cs-cl

Stable Reasoning, Unstable Responses: Mitigating LLM Deception via Stability Asymmetry

arXiv:2603.26846v2 Announce Type: replace-cross Abstract: As Large Language Models (LLMs) expand in capability and application scope, their trustworthiness becomes critical. A vital risk is intrinsic

safetyarxiv-cs-ai

TSAQA: Time Series Analysis Question And Answering Benchmark

arXiv:2601.23204v2 Announce Type: replace Abstract: Time series data are integral to critical applications across domains such as finance, healthcare, transportation, and environmental science. While

WorldBench: A Challenging and Visually Diverse Multimodal Reasoning Benchmark

model-releasesarxiv-cs-cv

arXiv:2606.06538v1 Announce Type: new Abstract: In real-world applications, models are expected to perform reliably across diverse settings. Yet, many existing multimodal benchmarks expand task types