Search: “applications”

arXiv:2604.21061v1 Announce Type: new Abstract: The application of artificial intelligence (AI) in IVF has shown promise in improving consistency and standardization of decisions, but often relies on

arXiv:2604.21279v1 Announce Type: new Abstract: Facial attribute editing and style manipulation are crucial for applications like virtual avatars and photo editing. However, achieving precise control

Replit implements a defense-in-depth security strategy to protect user applications across multiple architectural layers of their platform. The blog post details the security measures and protocols Re

arXiv:2604.21096v1 Announce Type: cross Abstract: Tip-of-the-Tongue (ToT) retrieval benchmarks have largely focused on English, limiting their applicability to multilingual information access. In this

arXiv:2604.21765v1 Announce Type: new Abstract: Data is a central resource for modern enterprises, and data validation is essential for ensuring the reliability of downstream applications. However, ex

arXiv:2604.20860v1 Announce Type: cross Abstract: Despite the success of Retrieval-Augmented Generation (RAG) in grounding LLMs with external knowledge, its application over heterogeneous sources (e.g

arXiv:2505.16737v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have achieved remarkable success across many applications, but their ability to generate harmful content raises s

arXiv:2604.21130v1 Announce Type: new Abstract: Autonomous Unmanned Aerial Vehicles (UAVs) have revolutionized industries through their versatility with applications including aerial surveillance, sea

Cloudsmith Inc., a startup that helps software teams manage application components, has secured 72 million in new funding. The Series C round was led by TCV, which was also the biggest backer of the c

arXiv:2604.21214v1 Announce Type: cross Abstract: Text-to-SQL models have significantly improved with the adoption of Large Language Models (LLMs), leading to their increasing use in real-world applic

arXiv:2604.21700v1 Announce Type: cross Abstract: The growing application of large language models (LLMs) in safety-critical domains has raised urgent concerns about their security. Many recent studie

arXiv:2604.21003v1 Announce Type: new Abstract: AI agents are increasingly deployed on complex, domain-specific workflows -- navigating enterprise web applications that require dozens of clicks and fo

Replit enables users to add mobile applications to their projects after importing them, with additional documentation available on their mobile development page. This feature allows developers to exte

arXiv:2604.20813v1 Announce Type: new Abstract: Transformer-based OCR models have shown strong performance on Latin and CJK scripts, but their application to African syllabic writing systems remains l

Amazon Quick changes how you work. You can set it up in minutes and by the end of the day, you will wonder how you ever worked without it. Quick connects with your applications, tools, and data, creat

arXiv:2507.14491v3 Announce Type: replace-cross Abstract: In many applications, one needs to learn a dynamical system from its solutions sampled at a finite number of time points. The learning problem

arXiv:2601.06606v2 Announce Type: replace-cross Abstract: We demonstrate CEDAR, an application for automating data science (DS) tasks with an agentic setup. Solving DS problems with LLMs is an underex

arXiv:2509.03740v3 Announce Type: replace-cross Abstract: Vision-language models (VLMs) like CLIP have shown impressive zero-shot and few-shot learning capabilities across diverse applications. Howeve

LangChain, an open-source framework for developing applications with large language models, is recruiting new team members as shared by co-founder Harrison Chase on X (Twitter). The careers page invit

Harrison Chase, co-founder and CEO of LangChain, appeared in a startup spotlight interview with Stephanie Wong. The discussion likely covered LangChain's development, its applications in AI and langua

arXiv:2604.20098v1 Announce Type: new Abstract: Large Language Models (LLMs) frequently hallucinate, limiting their reliability in critical applications. Conformal Prediction (CP) addresses this by ca

arXiv:2508.17761v3 Announce Type: replace Abstract: In safety-critical applications data-driven models must not only be accurate but also provide reliable uncertainty estimates. This property, commonl

arXiv:2604.19763v1 Announce Type: cross Abstract: Speech Emotion Recognition (SER) systems have growing applications in sensitive domains such as mental health and education, where biased predictions

arXiv:2407.11933v4 Announce Type: replace Abstract: Target-group detection is the task of detecting which group(s) a piece of content is ``directed at or about''. Applications include targeted marketi

arXiv:2411.00585v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have become foundational in modern language-driven software applications, profoundly influencing daily life. A cr

arXiv:2508.15411v3 Announce Type: replace-cross Abstract: Generative AI (GenAI) has emerged as a transformative technology, demonstrating remarkable capabilities across diverse application domains. Ho

arXiv:2604.19806v1 Announce Type: cross Abstract: Accurate prediction of energy and forces for 3D molecular systems is one of fundamental challenges at the core of AI for Science applications. Many po

arXiv:2508.01575v2 Announce Type: replace Abstract: Long-term time series forecasting (LTSF) underpins critical applications from energy management to weather prediction, yet achieving reliable multi-

arXiv:2604.19989v1 Announce Type: new Abstract: With modern defense applications increasingly relying on inexpensive, small Unmanned Aerial Vehicles (UAVs), a major challenge lies in designing intelli

arXiv:2604.20666v1 Announce Type: cross Abstract: Effective retrieval-augmented generation across bilingual Greek--English applications requires embedding models capable of capturing both domain-speci

arXiv:2602.20537v3 Announce Type: replace Abstract: Spatiotemporal predictive learning (STPL) aims to forecast future frames from past observations and is essential across a wide range of applications

arXiv:2603.25132v2 Announce Type: replace Abstract: Robust principal component analysis (RPCA) seeks a low-rank component and a sparse component from their summation. Yet, in many applications of inte

arXiv:2604.20245v1 Announce Type: cross Abstract: Fundamental rate-distortion-perception (RDP) trade-offs arise in applications requiring maintained perceptual quality of reconstructed data, such as n

arXiv:2604.20161v1 Announce Type: new Abstract: Multi-task learning is effective for related applications, but its performance can deteriorate when the target sample size is small. Transfer learning c

Spark, a magic talking dog application, has launched on iOS, allowing users to interact with an AI character. The post documents the user experience of multiple people meeting and interacting with Spa

arXiv:2604.20216v1 Announce Type: new Abstract: Many applications of LLM-based text regression require predicting a full conditional distribution rather than a single point value. We study distributio

arXiv:2604.19233v1 Announce Type: new Abstract: Deep learning-based object detectors have achieved remarkable success across numerous computer vision applications, yet they continue to struggle with s

arXiv:2604.18957v1 Announce Type: new Abstract: Extracting standardized metallurgical metrics from microscopy images remains challenging due to complex grain morphology and the data demands of supervi

arXiv:2604.19309v1 Announce Type: cross Abstract: Qualitative coding relies on a researcher's application of codes to textual data. As coding proceeds across large datasets, interpretations of codes o

Pinecone hosted a live broadcast event on X (formerly Twitter) inviting developers to build applications using their vector database platform. The stream likely covered Pinecone's capabilities, use ca

To act at the speed of business, AI agents must operate in fast and trusted reasoning loops. They need to “think” by reasoning across both your historical context and your live operational reality. On

The era of agentic AI is accelerating from human- to machine-speed operations, while also creating profound stress on legacy technology infrastructure. This new reality pushes foundational systems to

Last year at Google Cloud Next ‘25, we asked you to imagine a new future for AI. At Next ‘26, the question before you is how do you move AI into production across your entire enterprise? According to

arXiv:2604.18831v1 Announce Type: new Abstract: Frame-wise semantic segmentation of indoor lidar scans is a fundamental step toward higher-level 3D scene understanding and mapping applications. Howeve

arXiv:2604.18936v1 Announce Type: cross Abstract: Despite the growing application of Large Language Models (LLMs) to theoretical physics, there is little academic exploration into how domain-specific

NVIDIA AI and accelerated computing are advancing sustainability, climate science and energy efficiency through five key applications. These include RecycleOS, an AI and robotics solution that helps r