The pharmaceutical retail chain does not have a technology problem. It has a coordination problem that technology has never properly addressed. Walk into any mid-size pharmacy chain’s back office and you find the same pattern: remittance submitted on a spreadsheet at the end of the day, procurement triggered by a manager’s judgment when shelves look thin, supplier payments sitting in a queue waiting for someone to review the invoice. Branch A is out of Amoxicillin. Branch B is […]

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In federated learning (FL), decentralized model training allows multi-ple participants to collaboratively improve a shared machine learning model without exchanging raw data. However, ensuring the integrity and reliability of the system is challenging due to the presence of potentially malicious or faulty nodes that can degrade the model’s performance. This paper proposes a novel trust-based incentive mechanism designed to evaluate and reward the quality of contributions in FL systems. By dynamically assessing trust scores based on fac-tors such […]

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arXiv:2604.09818v1 Announce Type: new Abstract: Mycorrhizal fungi are vital to terrestrial ecosystem functioning. Yet monitoring their biodiversity at landscape scales is often unfeasible due to time and cost constraints. Current predictions suggest that 90% of mycorrhizal diversity hotspots remain unprotected, opening questions of how to broadly and effectively map underground fungal communities. Here, we show that self-supervised learning (SSL) applied to satellite imagery can predict below-ground ectomycorrhizal fungal richness across diverse environments. Our models explain over half the […]

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arXiv:2603.12483v1 Announce Type: new Abstract: Across many domains (e.g., IoT, observability, telecommunications, cybersecurity), there is an emerging adoption of conversational data analysis agents that enable users to “talk to your data” to extract insights. Such data analysis agents operate on timeseries data models; e.g., measurements from sensors or events monitoring user clicks and actions in product analytics. We evaluate 6 popular data analysis agents (both open-source and proprietary) on domain-specific data and query types, and find that they […]

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:::info Astounding Stories of Super-Science October 2022, by Astounding Stories is part of HackerNoon’s Book Blog Post series. You can jump to any chapter in this book here. THE MURDER OF ROGER ACKROYD – AN EVENING AT MAH JONG Astounding Stories of Super-Science October 2022: THE MURDER OF ROGER ACKROYD – AN EVENING AT MAH JONG By Agatha Christie ::: That night we had a little Mah Jong party. This kind of simple entertainment is very popular in King’s Abbot. […]

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arXiv:2606.06502v1 Announce Type: new Abstract: As large language models (LLMs) are increasingly trained on scraped web corpora without authorisation, content owners require forensic methods to prove that their documents were included in a model’s training set. We propose textbf{SIGIL} (textbf{S}ubtle textbf{I}njection for textbf{G}round-truth textbf{I}nference of textbf{L}LM training data), a framework that embeds imperceptible emph{canary sequences} into protected text and code such that any LLM trained on those documents exhibits statistically detectable behavioural signatures when probed with targeted queries. […]

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arXiv:2604.14265v1 Announce Type: new Abstract: We study behavior-regularized reinforcement learning (RL), where regularization toward a reference distribution (the dataset in offline RL or the base model in LLM RL finetuning) is essential to prevent value over-optimization caused by erroneous out-of-distribution extrapolation. Existing methods either rely on reparameterized policy gradient, which are difficult to scale to large generative models, or on reject sampling, which can be overly conservative when attempting to move beyond the behavior support. In this paper, […]

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