Knowledge catalogue
arXiv:2605.02260v1 Announce Type: cross Abstract: Comparing conditional distributions is a fundamental challenge in statistics and machine learning, with applications across a wide range of domains. W
arXiv:2605.01417v1 Announce Type: new Abstract: Evaluating large language models (LLMs) for medical applications remains challenging due to benchmark saturation, limited data accessibility, and insuff
arXiv:2602.04509v4 Announce Type: replace Abstract: Fine-tuning Multimodal Large Language Models (MLLMs) on task-specific data is an effective way to improve performance on downstream applications. Ho
arXiv:2605.02675v1 Announce Type: cross Abstract: This paper introduces an extension of generalised filtering for online applications. Generalised filtering refers to data assimilation schemes that jo
arXiv:2605.02069v1 Announce Type: new Abstract: Many scoring applications require absolute predictions, while pairwise comparisons can provide a simpler learning objective. We present Pair2Score, a tw
Parllama is a TUI (Text UI) application designed for easy management and use of Ollama-based LLMs that also works with major cloud-provided LLMs. It provides core model management features including f
arXiv:2605.01746v1 Announce Type: new Abstract: Single-image 3D face reconstruction is a core problem in computer vision, with important clinical applications such as cephalometric landmark analysis i
arXiv:2404.11277v2 Announce Type: replace-cross Abstract: In this paper we present a study of the applicability and feasibility of quantum-inspired algorithms and techniques in tensor networks for ind
arXiv:2605.00886v1 Announce Type: new Abstract: Infrared small target detection (IRSTD) plays a pivotal role in a broad spectrum of mission-critical applications, including maritime surveillance, mili
arXiv:2605.00382v2 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly deployed to generate code for human-centered applications where demographic fairness is critical. Howeve
arXiv:2605.02258v1 Announce Type: new Abstract: Vision Foundation Models (VFMs) pretrained on large-scale RGB data have demonstrated remarkable representation quality, yet their applicability to multi
arXiv:2510.05950v2 Announce Type: replace Abstract: Time series classification (TSC) spans diverse application scenarios, yet labeled data are often scarce, making task-specific training costly and in
arXiv:2602.22480v2 Announce Type: replace-cross Abstract: An important emerging application of coding agents is agent optimization: the iterative improvement of a target agent through edit-execute-eva
arXiv:2605.01018v1 Announce Type: new Abstract: Using multimodal foundation models to analyze table images is a high-value yet challenging application in consumer and enterprise scenarios. Despite its
arXiv:2605.00374v1 Announce Type: new Abstract: Edge classification, a crucial task for graph applications, remains relatively under-explored compared to link prediction. Current methods often overloo
This article from Latent Space likely explores the distinction between AI systems designed for general-purpose utility versus those optimized for specific alternative applications or use cases. The pi
I cannot provide a factual summary without access to the actual form content. This appears to be an application form shared by ComfyUI on X (Twitter), likely for a program, position, or opportunity re
arXiv:2603.03565v2 Announce Type: replace-cross Abstract: Conversational shopping assistants (CSAs) represent a compelling application of agentic AI, but moving from prototype to production reveals tw
arXiv:2605.00059v1 Announce Type: new Abstract: Deep reinforcement learning (DRL) finds extensive application in autonomous drone navigation within complex, high-risk environments. However, its practi
arXiv:2605.00698v1 Announce Type: cross Abstract: Federated learning (FL) holds great potential for medical applications. However, statistical heterogeneity across healthcare institutions poses a majo
arXiv:2605.00678v1 Announce Type: new Abstract: Aerosol Optical Depth (AOD) retrieval is essential for Earth observation, supporting applications from air quality monitoring to climate studies. Conven
arXiv:2605.00436v1 Announce Type: new Abstract: Concerns with the safety and reliability of applying large-language models (LLMs) in unpredictable real-world applications motivate this study, which ex
arXiv:2505.13007v2 Announce Type: replace Abstract: The ability to accurately model random fields plays a critical role in science and engineering for problems involving uncertain, spatially-varying q
arXiv:2605.00781v1 Announce Type: new Abstract: 3D world generation is essential for applications such as immersive content creation or autonomous driving simulation. Recent advances in 3D world gener
arXiv:2605.00600v1 Announce Type: cross Abstract: Deep neural networks achieve impressive results across diverse applications, yet their overconfidence on unseen inputs necessitates reliable epistemic
arXiv:2605.00146v1 Announce Type: new Abstract: Real-time object detection on energy-constrained platforms is critical for applications such as UAV-based inspection, autonomous navigation, and mobile
arXiv:2602.07744v3 Announce Type: replace Abstract: Diffusion and flow models have become the dominant paradigm for generative modeling on Riemannian manifolds, with successful applications in protein
arXiv:2605.00362v1 Announce Type: new Abstract: Multi-object tracking (MOT) is critical in numerous real-world applications, including surveillance, autonomous driving, and robotics. Accurately predic
Sam Altman announced on X that OpenAI would provide something special for applicants who couldn't attend the GPT-5.5 party due to space limitations. The post suggests OpenAI is offering a consolation
A developer is seeking beta testers for 'Ollama Cloud Chat,' an Android application that integrates Ollama's cloud models with a mobile chat interface. The post likely discusses features, how to parti
A Mac application has been released on GitHub (whatcable) that likely helps users identify or manage cables, possibly providing information about cable types, connectors, or compatibility. The project
arXiv:2402.14532v2 Announce Type: replace Abstract: Obtaining heteroscedastic predictive uncertainties from a Bayesian Neural Network (BNN) is vital to many applications. Often, heteroscedastic aleato
arXiv:2604.27704v1 Announce Type: new Abstract: In the segmentation of remotely sensed images, deep learning models are typically pre-trained using large image databases like ImageNet before fine-tune
arXiv:2604.27325v1 Announce Type: new Abstract: EigenDecomposition (ED) is at the heart of many computer vision algorithms and applications. One crucial bottleneck limiting its usage is the expensive
arXiv:2604.28078v1 Announce Type: new Abstract: Despite rapid advances in photorealistic video generation, real-world applications such as filmmaking require video aesthetics, e.g., harmonious colors
arXiv:2604.27543v1 Announce Type: new Abstract: Evaluating English ASR systems for conversational AI applications remains difficult, as many publicly available corpora are either pre-segmented into sh
arXiv:2604.27218v1 Announce Type: new Abstract: Person re-identification (ReID) systems that match individuals across images or video frames are essential in many real-world applications. However, exi
arXiv:2512.22046v2 Announce Type: replace Abstract: Prompt-driven Video Segmentation Foundation Models (VSFMs), such as SAM2, are increasingly used in applications including autonomous driving and dig
arXiv:2604.27277v1 Announce Type: cross Abstract: Brain MRI underpins a wide range of neuroscientific and clinical applications, yet most learning-based methods remain task-specific and require substa
arXiv:2506.09110v3 Announce Type: replace Abstract: Electroencephalography (EEG) provides real-time insights into brain activity and supports diverse applications in neuroscience. While EEG foundation
arXiv:2604.26962v1 Announce Type: cross Abstract: Education represents one of the most promising real-world applications for Large Language Models (LLMs). However, conventional tutoring systems rely o
arXiv:2604.28118v1 Announce Type: cross Abstract: Transformer models are widely deployed in critical AI applications, yet faults in their attention mechanisms, projections, and other internal componen
arXiv:2506.07180v3 Announce Type: replace-cross Abstract: As video large language models (Video-LLMs) become increasingly integrated into real-world applications that demand grounded multimodal reason
arXiv:2510.20933v2 Announce Type: replace-cross Abstract: Medical image segmentation is essential for clinical applications such as disease diagnosis, treatment planning, and disease development monit
Freely is a lightweight (~10 MB) desktop overlay application designed to enhance work and meetings by providing AI-powered features including system audio capture, screenshot functionality, and integr
arXiv:2604.27353v1 Announce Type: new Abstract: Gait recognition has emerged as a compelling biometric modality for surveillance and security applications, offering inherent advantages such as non-int
Elon Musk highlighted agent mode on Grok Imagine as a significant advancement in generative AI applications. Agent mode appears to enable more autonomous and sophisticated capabilities for AI image ge
arXiv:2604.27981v1 Announce Type: cross Abstract: Multivariate time series forecasting plays a pivotal role in numerous real-world applications, including financial analysis, energy management, and tr
This post likely discusses Jacob Effron's detailed analysis of AI agents and their applications across various domains beyond current mainstream use cases. The writeup, shared on Latent Space (a newsl
arXiv:2604.27713v1 Announce Type: new Abstract: The risks posed by AI features are increasing as they are rapidly integrated into software applications. In response, regulations and standards for safe
arXiv:2604.27505v1 Announce Type: new Abstract: While Reinforcement Learning from Human Feedback (RLHF) has become a pivotal paradigm for text-to-image generation, its application to image editing rem
arXiv:2507.14719v2 Announce Type: replace Abstract: As large language models (LLMs) become increasingly integrated into real-world applications, scalable and rigorous safety evaluation is essential. T
arXiv:2604.27617v1 Announce Type: cross Abstract: With the widespread application of Unmanned Aerial Vehicles (UAVs) in bridge structural health monitoring, deep learning-based automatic crack detecti
Runway has released an Android version of its application, making its AI video generation and editing tools available to Android users. This announcement represents an expansion of Runway's platform a
arXiv:2601.19216v2 Announce Type: replace-cross Abstract: The emerging applications of next-generation wireless networks demand high-fidelity environmental intelligence. 3D radio maps bridge physical
arXiv:2412.13682v5 Announce Type: replace Abstract: Travel planning stands out among real-world applications of Language Agents because it couples significant practical demand with a rigorous constrai
arXiv:2503.02332v3 Announce Type: replace-cross Abstract: Accurate segmentation of 3D vascular structures is essential for various medical imaging applications. The dispersed nature of vascular struct
arXiv:2603.03239v2 Announce Type: replace Abstract: Earth observation applications increasingly rely on data from multiple sensors, including optical, radar, elevation, and land-cover. Relationships b
arXiv:2604.26478v1 Announce Type: new Abstract: Hyperspectral imaging (HSI) semantic segmentation typically relies on in-domain training, but limited data availability often restricts model performanc
arXiv:2207.06229v3 Announce Type: replace-cross Abstract: Massive vector field datasets are common in multi-spectral optical and radar sensors, among many other emerging areas of application. We devel