Search: “applications”

Continuous-time reinforcement learning for optimal switching over multiple regimes

model-releasesarxiv-cs-lg

arXiv:2512.04697v3 Announce Type: replace-cross Abstract: This paper studies the continuous-time reinforcement learning (RL) for optimal switching problems across multiple regimes. We consider a type

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EgoGVAE: Ego-body Mesh Reconstruction via Guided Variational Autoencoder

DGX agent

arXiv:2607.27755v1 Announce Type: new Abstract: We address the problem of recovering the full-body mesh from only the head pose. This task has become essential for various applications based on head-m

model-releasesarxiv-cs-cv

31 Jul 2026

Explaining Image Similarity with Automatically Extracted Concept Activation Vectors

arXiv:2607.28386v1 Announce Type: new Abstract: Image similarity underlies many computer vision applications, yet it is often unclear why two images receive a high or low similarity score. Existing ex

local-aiarxiv-cs-cv

Generalization and Trade-off in Adversarial Training: An RKHS Perspective via Kernel Integral Operators

model-releasesarxiv-cs-lg

arXiv:2607.27995v1 Announce Type: cross Abstract: Adversarial training has emerged as a powerful approach for protecting models against adversarial attacks in a broad range of real-world applications.

Hierarchical Multilevel Monte Carlo for Order-Optimal Neural Actor-Critic in Average-Reward CMDPs

arXiv:2607.28390v1 Announce Type: new Abstract: Constrained Markov Decision Processes (CMDPs) provide a natural framework for reinforcement learning in safety-critical applications, where agents maxim

safetyarxiv-cs-lg

IFHierBench: Hierarchical Instruction Following for Large Language Models

model-releasesarxiv-cs-cl

arXiv:2607.27912v1 Announce Type: cross Abstract: Instruction-following ability is critical for deploying large language models in real-world applications, where downstream components depend on the ou

New research from Microsoft. This one is on training computer-use agents at scale. Recent pipelines generate synthetic environments in bulk,…

New research from Microsoft. This one is on training computer-use agents at scale. Recent pipelines generate synthetic environments in bulk, which moved the bottleneck from how many exist to what is i

model-releasesdair-ai--x

S-Avatar: Diffusion-Guided Gaussian Head Avatars from a Single Image

arXiv:2607.28164v1 Announce Type: new Abstract: We propose S-Avatar, a novel method for generating photorealistic 3D head avatars from a single image using a diffusion-guided 3D model generation modul

Sparsity Induced Identifiability in Matrix Tri-Factorisation

arXiv:2607.27507v1 Announce Type: new Abstract: Matrix factorisation is a fundamental tool for exploiting low-dimensional structure in high-dimensional data, with applications such as data compression

Toward Multi-Modal Deep Learning for Pulmonary Disease Classification: A Texture-Based Machine Learning Pilot Study on Public Chest X-Ray Data

arXiv:2607.27286v1 Announce Type: cross Abstract: Automated classification of pulmonary disease from chest radiographs is a widely studied application of machine learning in medical imaging. This pape

Unifying Adversarially Robust Model Experts in Vision-Language Models

arXiv:2607.27897v1 Announce Type: new Abstract: Vision-language models (VLMs), such as CLIP, are vulnerable to adversarial attacks, posing a serious problem for real-life applications and deployment.

safetyarxiv-cs-cv

World Action Planner: Generalizable Decision-Making with Action-Conditioned World Models

arXiv:2607.27599v1 Announce Type: cross Abstract: Building generalizable agents for diverse applications remains a fundamental challenge. While imitation learning-based policies succeed in specific tr

safetyarxiv-cs-ro

Agents

Do more with less: How GKE can reduce your cost per agent by 75%

In today’s agentic era, modern cloud applications are evolving from a set of passive tools to fleets of autonomous digital workers that reason, plan, and take action across a wide range of tasks. For

agentsgoogle-cloud-ai

Gated Adaptation for Continual Learning in Human Activity Recognition

model-releasesarxiv-cs-lg

arXiv:2603.10046v2 Announce Type: replace Abstract: Wearable sensors in Internet of Things (IoT) ecosystems increasingly support applications such as remote health monitoring, elderly care, and smart

Harnessing Large Language Models for Intelligent Resource Allocation in the Internet of Everything

arXiv:2607.26602v1 Announce Type: cross Abstract: The rapid development of the Internet of Everything (IoE) is accelerating the adoption of intelligent applications. However, the massive number of con

High-Order Markov Blanket Discovery via a k-Order Relaxation of the Faithfulness Assumption

arXiv:2607.26357v1 Announce Type: new Abstract: The problem of learning the graphical Markov blanket (MB) of a variable from data has applications in many areas such as structure learning for Bayesian

Multimodal fusion of visual and morphometric features for avian bone classification

arXiv:2607.26743v1 Announce Type: new Abstract: Artificial intelligence has shown considerable potential for archaeological applications, yet its use in zooarchaeology remains limited, particularly fo

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions

arXiv:2607.26467v1 Announce Type: new Abstract: Traffic prediction is a core task in intelligent transportation systems, supporting applications such as adaptive signal control, route guidance, and ri

Physically Real-time Infrared Attack against Optical Flow Estimation Networks

arXiv:2607.26651v1 Announce Type: new Abstract: With the promising performance of deep neural networks on image-based tasks, different real-world applications such as autonomous driving and motion det

safetyarxiv-cs-cv

Agents

RAG-HAR+: Towards Cost-Efficient LLM-Based Human Activity Recognition for Edge Deployment

arXiv:2607.26631v1 Announce Type: new Abstract: Human Activity Recognition (HAR) from wearable sensors supports applications in healthcare, rehabilitation, fitness tracking, and smart environments. Ye

agentsarxiv-cs-lg

Ripple: Real-Time Streaming Audio-Video Generation With Cross-Modal Recurrent Memory

arXiv:2607.26818v1 Announce Type: new Abstract: Audio-video generative models achieve impressive quality but suffer from high latency, making them unsuitable for real-time applications. Although sever

tutorialsarxiv-cs-cv

SeasonStereo: Robust Dense Stereo Matching for Multi-Date Satellite Imagery via Generative AI

arXiv:2607.27139v1 Announce Type: new Abstract: Accurate 3D reconstruction from satellite imagery typically relies on near-simultaneous stereo pairs, limiting its applicability to diachronic settings

SENSE: Efficient EEG-to-Text via Privacy-Preserving Semantic Retrieval

arXiv:2603.17109v2 Announce Type: replace Abstract: Decoding brain activity into natural language is a major challenge in AI with important applications in assistive communication, neurotechnology, an

local-aiarxiv-cs-lg

Step-Attention Refinement of DINOv3 Features for Efficient Anterior Eye Segmentation

arXiv:2607.27087v1 Announce Type: new Abstract: Anterior eye segment (AES) segmentation is a key component of both ocular biometrics and emerging clinical image analysis applications. However, heterog

Visibility-Aware Cooperative Tracking with Decentralized LiDAR-Based Aerial Swarms

arXiv:2512.01280v2 Announce Type: replace Abstract: Autonomous aerial tracking with drones offers vast potential for surveillance, cinematography, and industrial inspection applications. While single-

safetyarxiv-cs-ro

A Cost-Effective Multimodal LLM Reasoning Framework for Question Answering over Irregular Clinical Time Series

arXiv:2607.25947v1 Announce Type: new Abstract: Question answering (QA) over irregular clinical time series (ICTS) plays a pivotal role in a wide range of healthcare applications. Although recent mult

AMRD: Adaptive Multi-Teacher Relational Distillation for Lightweight Speech Emotion Recognition

arXiv:2607.25289v1 Announce Type: new Abstract: On-device speech emotion recognition (SER) is critical for real-time applications, yet large self-supervised models that excel at SER are too costly for

local-aiarxiv-cs-lg

Diffusion Disambiguation Models for Partial Label Learning

arXiv:2507.00411v2 Announce Type: replace Abstract: Learning from ambiguous labels is a long-standing problem in practical machine learning applications. The purpose of partial label learning (PLL) is

tutorialsarxiv-cs-lg

DocAnnot -- Accelerating the Creation of Key Information Extraction Datasets with GenAI-Powered Auto-annotation

arXiv:2607.24745v1 Announce Type: cross Abstract: Key Information Extraction (KIE) is vital for many document applications, but creating training datasets is traditionally a time-consuming manual proc

researcharxiv-cs-ai

DopQ-ViT: Towards Distribution-Friendly and Outlier-Aware Post-Training Quantization for Vision Transformers

arXiv:2408.03291v4 Announce Type: replace Abstract: Vision Transformers (ViTs) have gained significant attention, but their high computing cost limits the practical applications. While post-training q

Finding Optimal Cost-Bounded Plan Reductions: Refined Model

arXiv:2607.25484v1 Announce Type: new Abstract: In some real applications a plan may later become unfeasible due to newly imposed budget constraints, yet, at the same time, using only the original act

researcharxiv-cs-ai

Image Quality Dependent Degradation for AI Systems

arXiv:2607.25736v1 Announce Type: cross Abstract: Perception is one of the primary applications where neural networks outperform conventional algorithms. One example is AI systems for automated drivin

researcharxiv-cs-ai

Interactive Reward Agent: GUI Task Evaluation via Environment-State Verification

arXiv:2607.25904v1 Announce Type: new Abstract: Graphical user interface task evaluation aims to determine whether a GUI agent has successfully completed a user instruction. Automated GUI task evaluat

Online learning of subgrid-scale models for quasi-geostrophic turbulence in planetary interiors

arXiv:2511.14581v2 Announce Type: replace-cross Abstract: Machine learning approaches to subgrid-scale (SGS) modelling are now well established in atmospheric and oceanic applications. Among these, on

Hardware

Quasi-SVD: Learning a Lie-constrained matrix factorisation for real-time imaging

arXiv:2607.25967v1 Announce Type: new Abstract: Singular Value Decomposition (SVD) underlies matrix factorisation tasks across computational imaging, with medical applications increasingly demanding r

hardwarearxiv-cs-cv

Amortized Bayesian Causal Discovery of Extended Factor Graphs

arXiv:2607.22934v1 Announce Type: cross Abstract: Learning causal graphs from interventional data is a challenging problem with broad applications. In molecular biology, for example, a central goal is

Biggest ever MCP update brings metadata, cybersecurity enhancements

model-releasessiliconangle

The developers of the Model Context Protocol, an open-source technology that underpins many artificial intelligence applications, today released a new version of the software. The release is described

Hardware

Certified Parallel-in-Time Sinkhorn for Dynamic Entropic Optimal Transport

arXiv:2607.24741v1 Announce Type: cross Abstract: Dynamic applications, including optimal-transport Flow Matching, repeatedly solve related entropic optimal transport problems, yet conventional distri

hardwarearxiv-cs-lg

Agents

CodexGraph: Bridging Large Language Models and Code Repositories via Code Graph Databases

arXiv:2408.03910v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) excel in stand-alone code tasks like HumanEval and MBPP, but struggle with handling entire code repositories. Thi

agentsarxiv-cs-ai

DishSeg24k: A Large-Scale Benchmark for Food Segmentation with Stochastic Expert Decoding

model-releasesarxiv-cs-cv

arXiv:2607.23070v1 Announce Type: new Abstract: Food segmentation is essential for applications such as intelligent catering, dietary assessment, and recommendation. However, existing benchmarks fail

HandSCS: Structural Coordinate Space for Animatable Hand Gaussian Splatting

arXiv:2503.14736v3 Announce Type: replace Abstract: Photorealistic and animatable hand avatars are essential for applications such as AR/VR, gaming, and telepresence. Recent 3D Gaussian Splatting (3DG

Hiding in Plain Sight: An Effective Physical Adversarial Patch Attack against Visual-Infrared Fused Face Detection

arXiv:2607.23292v1 Announce Type: cross Abstract: Deep learning-based visual-infrared fused face detection models are increasingly deployed across a wide range of applications, yet they remain suscept

tutorialsarxiv-cs-cv

Impute On-Demand: Adaptive Correlated Time Series Imputation for Changing Environments

arXiv:2607.23503v1 Announce Type: cross Abstract: Internet of Things (IoT) applications generate vast amounts of Correlated Time Series (CTS) data that often contain missing values and require imputat

Invariant Discovery for Networked Systems

arXiv:2607.22944v1 Announce Type: cross Abstract: Invariants, the relations expected to hold among measured signals of a network, underpin applications from verification to traffic generation, telemet

tutorialsarxiv-cs-ai

KANEx: Translating Kolmogorov-Arnold Networks' Interpretability to Medical Explainability

arXiv:2607.24730v1 Announce Type: cross Abstract: Computer vision models have become highly effective for medical applications, yet their black-box nature continues to undermine clinician trust. In cl

local-aiarxiv-cs-ai

Manga Coloring Tool 2

local-air-stablediffusion

Hey everyone! 👋 I'm excited to announce the official release of Manga Coloring Tool 2.0, a completely free, local, open-source web application designed to colorize manga pages and chapters effortlessl

Neptuna: A Comprehensive Machine Learning Framework for Benchmarking Complex Multiphase Flows

arXiv:2607.22280v2 Announce Type: replace-cross Abstract: Compressible multiphase flows involving shocks and material interfaces arise in applications such as bubble collapse and droplet breakup, wher

Outcome-Fair Restless Multi-Armed Bandits for Stochastic Deadline Scheduling

arXiv:2607.23772v1 Announce Type: cross Abstract: We study a restless multi-armed bandit (RMAB) problem for a stochastic deadline scheduling application. RMAB problems are solved using the Whittle ind

safetyarxiv-cs-ai