arXiv:2603.02349v1 Announce Type: new Abstract: Metapopulation epidemic models are a valuable tool for studying large-scale outbreaks. With the limited availability of epidemic tracing data, it is challenging to infer the essential constituents of these models, namely, the epidemic parameters and the relevant mobility network between subpopulations. Either one of these constituents can be estimated while assuming the other; however, the problem of their joint inference has not yet been solved. Here, we propose two encoder-decoder deep learning architectures […]

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:::info Astounding Stories of Super-Science July, 2008, by Astounding Stories is part of HackerNoon’s Book Blog Post series. You can jump to any chapter in this book here. The Call of the Wild – The Toil of Trace and Trail Astounding Stories of Super-Science July 2008: The Call of the Wild – The Toil of Trace and Trail By Jack London ::: Thirty days from the time it left Dawson, the Salt Water Mail, with Buck and his mates […]

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Modern businesses run on digital trust. Customers expect their data to be safe, and partners expect operations to be reliable. To meet those expectations, security must be a daily practice, not a yearly project. This article walks through practical measures that reduce risk fast. Each section focuses on actions you can apply in most environments. The goal is simple – shrink the attack surface and strengthen your defences without adding needless complexity. Assessing Your Risk Landscape Start with […]

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arXiv:2602.21765v1 Announce Type: cross Abstract: Alignment and adaptation in large language models heavily rely on reinforcement learning from human feedback (RLHF); yet, theoretical understanding of its generalisability remains premature, especially when the learned reward could shift, and the KL control is estimated and clipped. To address this issue, we develop generalisation theory for RLHF that explicitly accounts for (1) emph{reward shift}: reward models are trained on preference data from earlier or mixed behaviour policies while RLHF optimises the […]

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arXiv:2604.14330v1 Announce Type: new Abstract: Mutual TLS (mTLS) provides strong, certificate-based authentication for both clients and servers, yet its adoption for user-facing websites remains rare. This paper presents a longitudinal study of mTLS usability, tracking 46 senior and graduate computer science students who configured client certificates from scratch, used them for routine authentication over a semester-long course, and managed credentials across multiple devices. The results reveal that initial setup is a major bottleneck; while daily use was considered […]

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arXiv:2604.08722v1 Announce Type: new Abstract: Sport analysis is crucial for team performance since it provides actionable data that can inform coaching decisions, improve player performance, and enhance team strategies. To analyze more complex features from game footage, a computer vision model can be used to identify and track key entities from the field. We propose the use of an object detection and tracking system to predict player positioning throughout the game. To translate this to positioning in relation […]

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arXiv:2604.06188v1 Announce Type: new Abstract: People increasingly hold sustained, open-ended conversations with large language models (LLMs). Public reports and early studies suggest that, in such settings, models can reinforce delusional or conspiratorial ideation or even amplify harmful beliefs and engagement patterns. We present an audit and benchmarking study that measures how different LLMs encourage, resist, or escalate disordered and conspiratorial thinking. We explicitly compare API outputs to user chat interfaces, like the ChatGPT desktop app or web interface, […]

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arXiv:2603.24761v1 Announce Type: new Abstract: Spreading and storing erasure-coded data in distributed systems effectively is challenging in real settings. Practical deployments must contend with unpredictable network latencies, particularly when information dispersal is integrated into consensus protocols, a prominent and latency-sensitive use case. Existing approaches address this challenge through timeout-based dissemination and adaptive communication or storage decisions driven by acknowledgments during dissemination. However, these designs focus almost exclusively on dissemination-time efficiency, complicate recovery with reconstruction procedures that require metadata […]

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