arXiv:2603.26712v1 Announce Type: new Abstract: Generative artificial intelligence (AI) is increasingly used to write and refactor research code, expanding computational workflows. At the same time, Green AI research has largely measured the footprint of models rather than the downstream workflows in which GenAI is a tool. We shift the unit of analysis from models to workflows and treat prompts as decision policies that allocate discretion between researcher and system, governing what is executed and when iteration stops. We […]

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arXiv:2603.15799v1 Announce Type: new Abstract: Prose2Policy (P2P) is a LLM-based practical tool that translates natural-language access control policies (NLACPs) into executable Rego code (the policy language of Open Policy Agent, OPA). It provides a modular, end-to-end pipeline that performs policy detection, component extraction, schema validation, linting, compilation, automatic test generation and execution. Prose2Policy is designed to bridge the gap between human-readable access requirements and machine-enforceable policy-as-code (PaC) while emphasizing deployment reliability and auditability. We evaluated Prose2Policy on the […]

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We study the distribution of regret in stochastic multi-armed bandits and episodic reinforcement learning through a unified framework. We formalize a distributional regret bound as a probabilistic guarantee that holds uniformly over all confidence levels $δin (0,1]$, thereby characterizing the regret distribution across the full range of $δ$. We present a simple UCBVI-style algorithm with exploration bonus $min{c_{1,k}/N, c_{2,k}/sqrt{N}}$, where $N$ denotes the visit count and $(c_{1,k},c_{2,k})$ are user-specified parameters. For arbitrary parameter sequences, we derive general gap-independent […]

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Banks have been operating worldwide for centuries, so it’s fair to wonder how money could work without them. That’s cryptocurrencies, by the way: money. A new type, a digital type, a decentralized type; specifically designed to be out of reach for banks, governments, and any other big central party.  Crypto networks, unlike banks, are systems that run day and night, across borders, with rules enforced by code rather than by a central authority. Let’s break this down. How […]

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arXiv:2511.02137v2 Announce Type: replace Abstract: Time-series forecasting increasingly demands not only accurate observational predictions but also causal forecasting under interventional and counterfactual queries in multivariate systems. We present DoFlow, a flow-based generative model defined over a causal Directed Acyclic Graph (DAG) that delivers coherent observational and interventional predictions, as well as counterfactuals through the natural encoding-decoding mechanism of continuous normalizing flows (CNFs). We also provide a supporting counterfactual recovery theory under certain assumptions. Beyond forecasting, DoFlow provides explicit […]

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arXiv:2601.14872v2 Announce Type: replace-cross Abstract: We study a linear observation model with an unknown permutation called textit{permuted/shuffled linear regression}, where responses and covariates are mismatched and the permutation forms a discrete, factorial-size parameter. The permutation is a key component of the data-generating process, yet its statistical investigation remains challenging due to its discrete nature. We develop a general statistical inference framework on the permutation and regression coefficients. First, we introduce a localization step that reduces the permutation space […]

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arXiv:2512.16383v2 Announce Type: replace-cross Abstract: Quantifying predictive uncertainty is essential for safe and trustworthy real-world AI deployment. Yet, fully nonparametric estimation of conditional distributions remains challenging for multivariate targets. We propose Tomographic Quantile Forests (TQF), a nonparametric, uncertainty-aware, tree-based regression model for multivariate targets. TQF learns conditional quantiles of directional projections $mathbf{n}^{top}mathbf{y}$ as functions of the input $mathbf{x}$ and the unit direction $mathbf{n}$. At inference, it aggregates quantiles across many directions and reconstructs the multivariate conditional distribution by […]

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