arXiv:2604.09698v1 Announce Type: new Abstract: The growing ubiquity of Extended Reality (XR) is driving Conversational Recommendation Systems (CRS) toward visually immersive experiences. We formalize this paradigm as Immersive CRS (ICRS), where recommended items are highlighted directly in the user’s scene-based visual environment and augmented with in-situ labels. While item recommendation has been widely studied, the problem of how to select and evaluate which information to present as immersive labels remains an open problem. To this end, we introduce […]

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arXiv:2602.16894v1 Announce Type: new Abstract: In response to the exponential growth in the use of artificial intelligence and machine learning applications, educators, researchers and policymakers have taken steps to integrate artificial intelligence applications into K-12 education. Among these efforts, one equally important approach has received little, if any attention: What if students and teachers were not just learning to be competent users of AI but also its creators? This question is at the heart of CreateAI in which […]

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arXiv:2603.26227v2 Announce Type: replace Abstract: We study privacy-preserving sparse linear regression in the high-dimensional regime, focusing on the LASSO estimator. We analyze two widely used mechanisms for differential privacy: output perturbation, which injects noise into the estimator, and objective perturbation, which adds a random linear term to the loss function. Using approximate message passing (AMP), we characterize the typical behavior of these estimators under random design and privacy noise. To quantify privacy, we adopt typical-case measures, including the […]

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Generative AI tools have lowered barriers to producing branded social media images and captions, yet small-business owners (SBOs) still struggle to create on-brand posts without access to professional designers or marketing consultants. Although these tools enable fast image generation from text prompts, aligning outputs with a brand’s intended look and feel remains a demanding, iterative creative task. In this position paper, we explore how SBOs navigate iterative content creation and how AI-assisted systems can support SBOs’ content creation […]

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arXiv:2604.18089v1 Announce Type: cross Abstract: Bayesian Deep Ensembles (BDEs) represent a powerful approach for uncertainty quantification in deep learning, combining the robustness of Deep Ensembles (DEs) with flexible multi-chain MCMC. While DEs are affordable in most deep learning settings, (long) sampling of Bayesian neural networks can be prohibitively costly. Yet, adding sampling after optimizing the DEs has been shown to yield significant improvements. This leaves a critical practical question: How long should the sequential sampling process continue to […]

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I have 61 post drafts queued up. 91 reply drafts. 18 finished blog posts, voice-matched and slop-filtered, ready to go. The distribution problem nobody talks about isn’t content scarcity – it’s the gap between a full queue and zero published output. That gap is where builder ambition goes to die quietly, surrounded by perfectly organized markdown files and automated scheduling daemons that never fire.

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arXiv:2601.15385v1 Announce Type: new Abstract: Natural-language-to-visualization (NL2VIS) systems based on large language models (LLMs) have substantially improved the accessibility of data visualization. However, their further adoption is hindered by two coupled challenges: (i) the absence of standardized evaluation metrics makes it difficult to assess progress in the field and compare different approaches; and (ii) natural language descriptions are inherently underspecified, so multiple visualizations may be valid for the same query. To address these issues, we introduce VegaChat, a […]

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We used machine learning and artificial intelligence: 1) to measure levels of peace in countries from news and social media and 2) to develop on-line tools that promote peace by helping users better understand their own media diet. For news media, we used neural networks to measure levels of peace from text embeddings of on-line news sources. The model, trained on one news media dataset also showed high accuracy when used to analyze a different news dataset. For […]

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Back in my student years, I had a book by a rather famous Dane about a rather famous programming language. And although I harbored genuine warm feelings for C++, I couldn’t get through even half of that book—the reading was that dreary. Well, it didn’t stop me from continuing to believe in the destiny fate had in store for me and C++. So, in the summer of 2011, I went to interview for a C++ developer. This is […]

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