technocracy

arXiv:2602.22274v1 Announce Type: new Abstract: Traffic flow forecasting has emerged as an indispensable mission for daily life, which is required to utilize the spatiotemporal relationship between each location within a time period under a graph structure to predict future flow. However, the large travel demand for broader geographical areas and longer time spans requires models to distinguish each node clearly and possess a holistic view of the history, which has been paid less attention to in prior works. […]

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arXiv:2602.17865v1 Announce Type: new Abstract: Time-series forecasting is a critical task across many domains, from engineering to economics, where accurate predictions drive strategic decisions. However, applying advanced deep learning models in challenging, volatile domains like finance is difficult due to the inherent limitation and dynamic nature of financial time series data. This scarcity often results in sub-optimal model training and poor generalization. The fundamental challenge lies in determining how to reliably augment scarce financial time series data to […]

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arXiv:2602.06146v1 Announce Type: cross Abstract: In recent work it is shown that Q-learning with linear function approximation is stable, in the sense of bounded parameter estimates, under the $(varepsilon,kappa)$-tamed Gibbs policy; $kappa$ is inverse temperature, and $varepsilon>0$ is introduced for additional exploration. Under these assumptions it also follows that there is a solution to the projected Bellman equation (PBE). Left open is uniqueness of the solution, and criteria for convergence outside of the standard tabular or linear MDP […]

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Amazon has been constantly changing users online shopping experience and this latest update shows that the company is moving toward more immersive, AI-driven experiences. “Hear the highlights” was the first step in letting shoppers listen to quick, podcast-like audio summaries of products. By adding “Join the chat,” Amazon is letting people turn that one-way listening session into a real conversation. Instead of searching through long product descriptions or reviews, people can listen, ask questions, and get answers personalized. […]

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The Marvel Cinematic Universe (MCU) has been ongoing since 2008. Dozens of tv shows and movies later, so many incredible characters have been introduced to the general public. Characters that were only known to comic book fans became worldwide icons. If you go anywhere in the world and say, “I am Groot,” there’s a good chance that somebody will get your reference. But even still, there are a ton of characters that have remained surprisingly unused. Here are […]

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BioLLM is a SmolLM2-360M distilled from co-training on live human neurons via Cortical Labs’ CL1 biocomputer. The neurons modulate token selection through real-time spike responses, and the distillation filters for moments of genuine neural integration. It’s not conscious — the creator’s own consciousness framework says so — but the data shows biological substrates exhibit self-organizing network topology and measurable integration growth that no software RNG can replicate. The token wasn’t his idea. The model is free on Hugging […]

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arXiv:2602.07120v1 Announce Type: new Abstract: Modern language models (LMs) tend to memorize portions of their training data and emit verbatim spans. When the underlying sources are sensitive or copyright-protected, such reproduction raises issues of consent and compensation for creators and compliance risks for developers. We propose Anchored Decoding, a plug-and-play inference-time method for suppressing verbatim copying: it enables decoding from any risky LM trained on mixed-license data by keeping generation in bounded proximity to a permissively trained safe […]

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A place to share your thoughts, prayers, and, most importantly (once the reviews are out, should be soon…), rants or maybe even some relieved comments. Good luck everyone! submitted by /u/WelcomeToFacism [link] [comments]

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arXiv:2602.09159v1 Announce Type: new Abstract: Recent multi-agent frameworks have broadened the ability to tackle oncology decision support tasks that require reasoning over dynamic, heterogeneous patient data. We propose Contribution-Aware Medical Multi-Agents (CoMMa), a decentralized LLM-agent framework in which specialists operate on partitioned evidence and coordinate through a game-theoretic objective for robust decision-making. In contrast to most agent architectures relying on stochastic narrative-based reasoning, CoMMa utilizes deterministic embedding projections to approximate contribution-aware credit assignment. This yields explicit evidence attribution […]

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arXiv:2604.18810v1 Announce Type: new Abstract: An algorithm for simulation of switching converters is proposed in the paper. The algorithm is based on simulation of averaged circuit model applying “switching cell” concept, and construction of instantaneous values of the waveforms using quasi steady state and linear ripple approximation. Simulation covers converters operating both in the continuous and the discontinuous conduction mode. Application of the algorithm is demonstrated by simulation results of all three of the basic converters: buck, boost […]

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