Knowledge catalogue
arXiv:2607.29617v1 Announce Type: cross Abstract: Imitation learning (IL)---training an agent to replicate expert behavior from demonstrations---underpins applications from robotics to language model
GitHub: https://github.com/Loann110/Vao2 Hello everyone, I’m currently developing Vao2, an open-source application that brings together news, YouTube channels, GitHub repositories and more (to be adde
arXiv:2607.27816v1 Announce Type: new Abstract: Role-playing agents (RPAs) have become one of the most important consumer applications of large language models. Users engage in multi-turn conversation
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
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
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
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.
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
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, which moved the bottleneck from how many exist to what is i
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
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
arXiv:2512.01280v2 Announce Type: replace Abstract: Autonomous aerial tracking with drones offers vast potential for surveillance, cinematography, and industrial inspection applications. While single-
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
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
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
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
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
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
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
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
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
arXiv:2607.25967v1 Announce Type: new Abstract: Singular Value Decomposition (SVD) underlies matrix factorisation tasks across computational imaging, with medical applications increasingly demanding r
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
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
arXiv:2607.24741v1 Announce Type: cross Abstract: Dynamic applications, including optimal-transport Flow Matching, repeatedly solve related entropic optimal transport problems, yet conventional distri
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
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
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
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
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
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
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
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
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
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
arXiv:2607.22877v1 Announce Type: new Abstract: With the emergence of Physical AI, artificial intelligence is extending beyond screen-based applications to embodied systems that perceive, interact wit
arXiv:2607.24274v1 Announce Type: cross Abstract: Inverse design of three-dimensional porous media is central to applications in filtration, catalysis, energy storage, fuel cells, thermal management,
arXiv:2607.24233v1 Announce Type: new Abstract: 3D reconstruction of unknown environments is a key application in robotics but is severely limited by the computational and energy capabilities of curre
arXiv:2607.23468v1 Announce Type: new Abstract: Real-time 6-DoF object pose tracking is essential for many robotics applications, and several approaches exist. Yet even today's approaches remain unrel
arXiv:2607.22806v1 Announce Type: new Abstract: Modern cloud deployments distribute applications across multiple geographic regions, yet standard routing mechanisms prioritize latency while ignoring t
arXiv:2307.14544v2 Announce Type: replace-cross Abstract: This paper presents an artificial intelligence tool designed to assist students with dyslexia, ADHD, and short attention spans in processing t
Workflow automation company Tines Security Services Ltd. today launched Tines 3B, an artificial intelligence-native platform for building, running and governing enterprise workflows, applications and
arXiv:2509.10058v2 Announce Type: replace Abstract: Accurate color alignment in text-to-image (T2I) generation is critical for applications such as fashion, product visualization, and interior design,
arXiv:2607.21904v1 Announce Type: cross Abstract: Image inpainting aims to reconstruct missing or corrupted regions of an image while preserving as much as possible, visual and semantic consistency. I