In the time it takes to watch a Netflix episode, I built a complete, on-chain video game. I’m a solo developer. My only partner was an AI copilot. And in about an hour, we built and deployed “Pixel Golf,” a 2D physics game running on the Avalanche blockchain. This isn’t just a fun experiment. It’s a blueprint for the future of game distribution — a future where “buying” a game means you actually, truly own it. The Problem with “Ownership” […]

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arXiv:2603.03785v1 Announce Type: new Abstract: Randomized Controlled Trials (RCTs) represent the gold standard for causal inference yet remain a scarce resource. While large-scale observational data is often available, it is utilized only for retrospective fusion, and remains discarded in prospective trial design due to bias concerns. We argue this “tabula rasa” data acquisition strategy is fundamentally inefficient. In this work, we propose Active Residual Learning, a new paradigm that leverages the observational model as a foundational prior. This […]

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arXiv:2601.05263v1 Announce Type: new Abstract: This short technical note presents a formal generalization of the Time Warp Edit Distance (TWED) proposed by Marteau (2009) to arbitrary metric spaces. By viewing both the observation and temporal domains as metric spaces $(X, d)$ and $(T, Delta)$, we define a Generalized TWED (GTWED) that remains a true metric under mild assumptions. We provide self-contained proofs of its metric properties and show that the classical TWED is recovered as a special case […]

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The life of a prescription at Amazon Pharmacy From pricing estimation and regulatory compliance to inventory management and chatbot assistants, machine learning models help Amazon Pharmacy customers stay healthy and save time and money. Conversational AI Alexandre Alves Anita Vila September 30, 01:32 PM October 02, 11:42 AM Pharmacies play a vital role in ensuring patients health, but the process of dispensing medications is far more complex than it may appear. At Amazon Pharmacy, we are using artificial […]

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arXiv:2601.03244v1 Announce Type: new Abstract: Many important problems in science and engineering involve inferring a signal from noisy and/or incomplete observations, where the observation process is known. Historically, this problem has been tackled using hand-crafted regularization (e.g., sparsity, total-variation) to obtain meaningful estimates. Recent data-driven methods often offer better solutions by directly learning a solver from examples of ground-truth signals and associated observations. However, in many real-world applications, obtaining ground-truth references for training is expensive or impossible. Self-supervised […]

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arXiv:2604.02395v1 Announce Type: new Abstract: We study illusion elimination problems on directed social networks where each vertex is colored either red or blue. A vertex is under textit{majority illusion} if it has more red out-neighbors than blue out-neighbors when there are more blue vertices than red ones in the network. In a more general phenomenon of $p$-illusion, at least $p$ fraction of the out-neighbors (as opposed to $1/2$ for majority) of a vertex is red. In the directed […]

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Table of Links Abstract and 1. Introduction Some recent trends in theoretical ML 2.1 Deep Learning via continuous-time controlled dynamical system 2.2 Probabilistic modeling and inference in DL 2.3 Deep Learning in non-Euclidean spaces 2.4 Physics Informed ML Kuramoto model 3.1 Kuramoto models from the geometric point of view 3.2 Hyperbolic geometry of Kuramoto ensembles 3.3 Kuramoto models with several globally coupled sub-ensembles Kuramoto models on higher-dimensional manifolds 4.1 Non-Abelian Kuramoto models on Lie groups 4.2 Kuramoto models […]

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The rapid evolution of data-driven fields demands educational paradigms that transition from static analysis to dynamic interaction with live information. This paper presents a novel technical framework, the Dual-Agent Curator-Tutor (DACT), which integrates Artificial Intelligence as a concurrent Real-Time Data Curator and Interactive Tutor within Immersive Analytics (IA) learning environments. The DACT framework features two synergistic AI agents: a Curation Agent that dynamically ingests, filters, and contextualizes live data streams (e.g., IoT, financial feeds) for pedagogical alignment, and […]

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arXiv:2604.09718v1 Announce Type: new Abstract: LLM-driven web agents operating through continuous inference loops — repeatedly querying a model to evaluate browser state and select actions — exhibit a fundamental scalability constraint for repetitive tasks. We characterize this as the Rerun Crisis: the linear growth of token expenditure and API latency relative to execution frequency. For a 5-step workflow over 500 iterations, a continuous agent incurs approximately 150.00 USD in inference costs; even with aggressive caching, this remains near […]

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