arXiv:2603.02366v1 Announce Type: new Abstract: Current AI writing tools, which rely on text prompts, poorly support the spatial and interactive nature of storytelling where ideas emerge from direct manipulation and play. We present PlayWrite, a mixed-reality system where users author stories by directly manipulating virtual characters and props. A multi-agent AI pipeline interprets these actions into Intent Frames -structured narrative beats visualized as rearrangeable story marbles on a timeline. A large language model then transforms the user’s assembled […]

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We invite you to read an article on how C++ is used in modern game development and why the industry is still not ready to move away from it. The author explores how C++ works at different levels of game engines and how performance requirements, legacy code, and platform constraints make an impact on the industry. We published and translated this article with the copyright holder’s permission. The author is Sergey Kushnirenko. I intended to write a follow-up […]

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arXiv:2602.09064v1 Announce Type: new Abstract: Open Source Software (OSS) projects follow diverse lifecycle trajectories shaped by evolving patterns of contribution, coordination, and community engagement. Understanding these trajectories is essential for stakeholders seeking to assess project organization and health at scale. However, prior work has largely relied on static or aggregated metrics, such as project age or cumulative activity, providing limited insight into how OSS sustainability unfolds over time. In this paper, we propose a hierarchical predictive framework that […]

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arXiv:2505.06835v3 Announce Type: replace-cross Abstract: Sliced optimal transport (SOT), or sliced Wasserstein (SW) distance, is widely recognized for its statistical and computational scalability. In this work, we further enhance computational scalability by proposing the first method for estimating SW from sample streams, called emph{streaming sliced Wasserstein} (Stream-SW). To define Stream-SW, we first introduce a streaming estimator of the one-dimensional Wasserstein distance (1DW). Since the 1DW has a closed-form expression, given by the absolute difference between the quantile functions […]

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arXiv:2601.12259v1 Announce Type: new Abstract: Building upon FutureX, which established a live benchmark for general-purpose future prediction, this report introduces FutureX-Pro, including FutureX-Finance, FutureX-Retail, FutureX-PublicHealth, FutureX-NaturalDisaster, and FutureX-Search. These together form a specialized framework extending agentic future prediction to high-value vertical domains. While generalist agents demonstrate proficiency in open-domain search, their reliability in capital-intensive and safety-critical sectors remains under-explored. FutureX-Pro targets four economically and socially pivotal verticals: Finance, Retail, Public Health, and Natural Disaster. We benchmark agentic Large […]

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arXiv:2603.00192v1 Announce Type: cross Abstract: In healthcare, predictive models increasingly inform patient-level decisions, yet little attention is paid to the variability in individual risk estimates and its impact on treatment decisions. For overparameterized models, now standard in machine learning, a substantial source of variability often goes undetected. Even when the data and model architecture are held fixed, randomness introduced by optimization and initialization can lead to materially different risk estimates for the same patient. This problem is largely […]

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Prompt injection. The bane of every developer building with LLMs. It’s not a bug in your code. It’s a sophisticated attack that exploits the very nature of how LLMs interpret and prioritize natural language instructions. If you’re still relying on keyword blacklists and static filters, you’re already losing the battle. Attackers aren’t just trying to override instructions anymore. They’re subtly redirecting models, influencing multi-step interactions, and generally making a mess of your carefully crafted AI applications. This isn’t […]

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arXiv:2601.16398v1 Announce Type: new Abstract: Algorithmic audits are essential tools for examining systems for properties required by regulators or desired by operators. Current audits of large language models (LLMs) primarily rely on black-box evaluations that assess model behavior only through input-output testing. These methods are limited to tests constructed in the input space, often generated by heuristics. In addition, many socially relevant model properties (e.g., gender bias) are abstract and difficult to measure through text-based inputs alone. To […]

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We are back with another Company of the Week feature! Every week, we share an awesome tech brand from our tech company database, making their evergreen mark on the internet. This unique HackerNoon database ranks S&P 500 companies and top startups of the year alike. This week, we are featuring Mezo, a company that transforms Bitcoin from a passive asset into a productive economic engine, allowing users to unlock liquidity through loans or earn yield without selling their holdings. By combining […]

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