Knowledge catalogue
Cursor has launched a feature enabling users to publish and share canvases—custom applications such as dashboards, reports, and internal tools—with their teams. This update extends Cursor's canvas fun
arXiv:2601.04120v2 Announce Type: replace-cross Abstract: Optimal control of obstacle problems arises in a wide range of applications and is computationally challenging due to its nonsmoothness, nonli
arXiv:2606.02755v1 Announce Type: cross Abstract: Large language model (LLM) applications are increasingly expected to satisfy deterministic institutional requirements while relying on probabilistic g
arXiv:2606.03774v1 Announce Type: new Abstract: Eye tracking is essential for smart glasses, as it provides insight into user attention for ambient intelligence applications. However, most existing ey
This Databricks article explores Apache Spark's real-time mode capabilities for gaming applications, specifically focusing on how to implement efficient real-time sessionization to group and analyze p
As your application evolves with new features, you should periodically re-run SEO scans to ensure optimal search engine visibility and track your app's traffic metrics to monitor performance and user
'Built with Grok' is a post from Elon Musk on X platform promoting or highlighting something created using Grok, xAI's large language model. The post likely showcases an application, feature, or capab
arXiv:2606.03827v1 Announce Type: cross Abstract: In-silico trials of medical devices require the generation of virtual populations of anatomies. In cardiovascular applications, virtual anatomy is typ
arXiv:2606.03695v1 Announce Type: new Abstract: As language models are increasingly deployed in real-world applications, the ability to erase specific knowledge from them becomes critical for safety a
This documentation page provides instructions for configuring the Ollama desktop application to work with Hermes models available through Ollama Cloud. It covers the setup process for integrating clou
arXiv:2602.04132v4 Announce Type: replace-cross Abstract: Reinforcement Learning (RL) has achieved remarkable success in solving complex sequential decision-making problems. However, its application t
arXiv:2308.07867v4 Announce Type: replace-cross Abstract: The absence of formal performance guarantees in machine learning (ML) has limited its adoption for safety-critical power system applications,
arXiv:2606.03402v1 Announce Type: new Abstract: Audio-driven human motion video generation aims to synthesize realistic and temporally coherent human animations from a single static image, with applic
arXiv:2509.01641v3 Announce Type: replace-cross Abstract: We propose a novel diffusion model, termed the non-identical diffusion model, and investigate its application to wireless orthogonal frequency
arXiv:2507.23035v4 Announce Type: replace Abstract: Large language models (LLMs) have demonstrated impressive capabilities across a wide range of applications, but demand substantial memory and comput
arXiv:2606.03521v1 Announce Type: cross Abstract: To improve the real-world applicability of reinforcement learning (RL), the field of adversarially robust RL studies how to train agents under adversa
PrivateGPT is back! In 2023, it became the first offline RAG implementation and a breakout open source project. Then we went quiet in 2024. Today, PrivateGPT 1.0 is here: a full application API layer
arXiv:2606.03858v1 Announce Type: new Abstract: Despite the pivotal role of numerical reasoning as the cornerstone of mathematical capabilities in large language models (LLMs) across applications, few
arXiv:2411.15851v2 Announce Type: replace Abstract: While vision-language models like CLIP have shown remarkable success in open-vocabulary tasks, their application is currently confined to image-leve
arXiv:2606.03406v1 Announce Type: new Abstract: Reliable correspondence estimation is a fundamental problem in image processing, underpinning applications such as Structure from Motion, visual localiz
arXiv:2606.03399v1 Announce Type: new Abstract: While large language models (LLMs) are increasingly used for clinical applications, many existing pipelines require sending raw sensitive health informa
arXiv:2606.03160v1 Announce Type: new Abstract: Recognizing human actions from point cloud sequences is critical for 3D perception driven applications such as autonomous driving and human-computer int
This post likely humorously describes the awkward situation where a user intends to paste a saved AI prompt into a tool or application, but accidentally pastes a text message from their clipboard inst
arXiv:2606.02822v1 Announce Type: cross Abstract: Production LLM applications stack several defense families -- refusal-phrase filters, token-budget controls, model allowlists, rate limits, tool-regis
arXiv:2606.00417v1 Announce Type: cross Abstract: To meet the stringent requirements of emerging applications and the increasingly complex network management and operation, the Next Generation Mobile
At Google Cloud Next, we announced the preview of graph algorithms with Spanner Graph, bringing Google Research’s state-of-the-art graph mining capabilities natively to your database. These graph inte
arXiv:2603.07578v2 Announce Type: replace Abstract: Event cameras offer high temporal resolution and low latency, making them ideal sensors for high-speed robotic applications where conventional camer
Nous Research announced the availability of Hermes Agent across all platforms through a desktop application accessible via the provided link. This release makes their Hermes Agent tool universally ava
Amazon Web Services Inc. today enhanced its database services to simplify the process of building and operating agentic artificial intelligence applications while also lowering the barriers to cloud m
arXiv:2606.01906v1 Announce Type: new Abstract: Emotions evolve through the dynamics of conversation, and understanding their transition structure is foundational to applications ranging from mental-h
arXiv:2606.01170v1 Announce Type: cross Abstract: The application of multi-agent systems in robotics is a very challenging field. Several competitions involving such systems are proposed to foster res
NVIDIA JetPack 7.2 enables deployment of AI agents to edge devices with optimized memory and performance for real-world applications. The release directly supports one-command deployment of NVIDIA Nem
arXiv:2606.01634v1 Announce Type: cross Abstract: Generating realistic time series is essential for scientific research and real-world applications. However, existing methods often emphasize overall d
arXiv:2606.00934v1 Announce Type: cross Abstract: Network data are ubiquitous across the social sciences, biology, and information systems. Generating realistic synthetic network data has broad applic
arXiv:2511.20615v2 Announce Type: replace-cross Abstract: This study aimed to explore the application of deep neural networks for whole-body human posture prediction during dynamic load-reaching activ
arXiv:2606.00083v1 Announce Type: cross Abstract: Reinforcement learning relies on accurate reward functions, which are often hand-crafted or even unavailable in real-world applications, such as robot
arXiv:2505.10882v2 Announce Type: replace Abstract: Principal component analysis classically requires full d-dimensional samples, yet in various applications hardware limits acquisition to a few scala
arXiv:2510.01891v2 Announce Type: replace-cross Abstract: Individual Head-Related Transfer Functions (HRTFs) are starting to be introduced in many commercial immersive audio applications and are cruci
arXiv:2410.14483v3 Announce Type: replace-cross Abstract: Reliable uncertainty quantification for causal effects is crucial in high-stakes applications, but remains challenging when the target is an e
arXiv:2606.01904v1 Announce Type: cross Abstract: The increasing application of Natural Language Processing (NLP) in healthcare demands language models specifically attuned to the complexities of clin
arXiv:2606.00260v1 Announce Type: new Abstract: Human Activity Recognition (HAR) from ambient sensors enables smart-home applications such as health monitoring and assisted living. In realistic deploy
arXiv:2606.01425v1 Announce Type: new Abstract: Mixed-combinatorial nonlinear programming (MCNLP) problems arise in many engineering design and planning applications, e.g., due to categorical, compone
arXiv:2606.01698v1 Announce Type: new Abstract: Deep learning has revolutionized medical image analysis, delivering exceptional diagnostic accuracy across diverse applications. Yet, the lack of interp
arXiv:2606.00605v1 Announce Type: new Abstract: Transformers have achieved remarkable success across a wide range of applications, and a growing body of work suggests that part of their strength comes
arXiv:2606.00049v1 Announce Type: cross Abstract: Large language models (LLMs) are widely recognised for their applications in natural language generation and are increasingly used for code generation
arXiv:2512.17605v2 Announce Type: replace-cross Abstract: Robust mammography registration is essential for clinically relevant applications like tracking disease progression in breast tissue. However,
Microsoft Corp. today introduced Rayfin, an open-source software development kit and command-line interface that lets developers and coding agents define an entire application backend in code and depl
arXiv:2606.02352v1 Announce Type: new Abstract: Robust self-supervised learning of multi-modal video representations is critical for real-world applications such as driver distraction detection, where
arXiv:2606.02341v1 Announce Type: cross Abstract: Underwater acoustic classification has a wide array of oceanic applications, but faces challenges due to an increasingly complex acoustic environment.
arXiv:2606.01947v1 Announce Type: cross Abstract: Research and applications in artificial intelligence have recently shifted with the rise of large pretrained models, which deliver state-of-the-art re
arXiv:2512.22702v2 Announce Type: replace Abstract: Deep learning models have grown popular in time series applications. However, the large quantity of newly proposed architectures and the often contr
arXiv:2507.08064v3 Announce Type: replace-cross Abstract: As multimedia content expands, the demand for unified multimodal retrieval (UMR) in real-world applications increases. Recent work leverages m
arXiv:2606.01620v1 Announce Type: new Abstract: Video diffusion models have significantly advanced portrait video generation, yet their high computational demands limit their use in interactive applic
arXiv:2310.15676v2 Announce Type: replace-cross Abstract: Multi-modal 3D Intelligence has gained considerable attention due to its wide applications in autonomous driving and world simulation, etc. Co
arXiv:2606.02328v1 Announce Type: new Abstract: We explore Riemannian optimization techniques for rank-factored matrix parameters, targeting contemporary deep learning applications. We examine ten poi
arXiv:2606.01689v1 Announce Type: cross Abstract: The detection and segmentation of infrared small targets have important application significance in the fields of surveillance and security, maritime
arXiv:2601.14323v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models are increasingly deployed in safety-critical robotic applications, yet their security vulnerabilities rema
arXiv:2606.02380v1 Announce Type: cross Abstract: As LLM-based agents expand their operational scope, reliability becomes a prerequisite for real-world deployment. However, in practical applications,
arXiv:2606.02518v1 Announce Type: new Abstract: Fine-grained image classification (FGIC) has broad applications and has attracted significant research attention. In this paper, we explore a novel para
arXiv:2509.16635v2 Announce Type: replace Abstract: In real applications, person re-identification (ReID) is expected to retrieve the target person at any time, including both daytime and nighttime, r