arXiv:2603.23831v1 Announce Type: cross Abstract: Deep neural networks (DNNs), particularly those using Rectified Linear Unit (ReLU) activation functions, have achieved remarkable success across diverse machine learning tasks, including image recognition, audio processing, and language modeling. Despite this success, the non-convex nature of DNN loss functions complicates optimization and limits theoretical understanding. In this paper, we highlight how recently developed convex equivalences of ReLU NNs and their connections to sparse signal processing models can address the challenges of training […]

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arXiv:2602.04927v1 Announce Type: new Abstract: Artificial intelligence systems introduce complex privacy risks throughout their lifecycle, especially when processing sensitive or high-dimensional data. Beyond the seven traditional privacy threat categories defined by the LINDDUN framework, AI systems are also exposed to model-centric privacy attacks such as membership inference and model inversion, which LINDDUN does not cover. To address both classical LINDDUN threats and additional AI-driven privacy attacks, PriMod4AI introduces a hybrid privacy threat modeling approach that unifies two structured […]

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I’m looking for a RL Agentic Framework that takes a Univariate feature and detects outlier data points by smartly choosing A statistical outlier detection method (Zscore, Modified Zscore, Percentile Capping, IQR) it’s threshold And mastering the art of over time. I’m new to RL and I need this for a project, so any suggestions will be highly appreciated. submitted by /u/Lumenbolt [link] [comments]

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arXiv:2604.17002v1 Announce Type: new Abstract: In visual analytics, applying filters to drill-down and extract higher-value insights is a common and important data analysis method. When the drill-down space becomes excessively large, analysts may lose orientation, leading to decreased efficiency in the drill-down process. To tackle these challenges, we propose the Intelligent Drill-Down Framework, in which a large language model (LLM) facilitates the generation of visual insights, leverages user interaction data to interpret user intent, and generates appropriate drill-down […]

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arXiv:2602.10143v1 Announce Type: new Abstract: Recently, few-shot learning (FSL) has become a popular task that aims to recognize new classes from only a few labeled examples and has been widely applied in fields such as natural science, remote sensing, and medical images. However, most existing methods focus only on the visual modality and compute prototypes directly from raw support images, which lack comprehensive and rich multimodal information. To address these limitations, we propose a novel Multimodal Prototype Augmentation […]

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AI-generated video has gone from novelty to creative tool almost overnight, and Runway has a front row seat to the shift. The New York-based company has raised close to $860 million at a $5.3 billion valuation, and its models are going toe-to-toe with the most well-funded labs in the world, including Google and OpenAI.   The technology goes way beyond […]

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As cryptocurrency adoption accelerates globally, the gap between traditional finance and Web3 remains one of the industry’s most persistent challenges. While blockchain infrastructure has matured dramatically, the simple act of converting fiat to crypto and back continues to create friction for millions of users and businesses. Ramp Network has spent eight years addressing this fundamental problem, building the financial pipes that connect 150+ countries to the crypto economy. In this interview, we sit down with Przemek Kowalczyk, co-founder […]

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arXiv:2604.16903v1 Announce Type: new Abstract: Collecting embodied interaction data at scale remains costly and difficult due to the limited accessibility of conventional interfaces. We present a gamified data collection framework based on Unity that combines procedural scene generation, VR-based humanoid robot control, automatic task evaluation, and trajectory logging. A trash pick-and-place task prototype is developed to validate the full workflow.Experimental results indicate that the collected demonstrations exhibit broad coverage of the state-action space, and that increasing task difficulty […]

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