arXiv:2512.09295v3 Announce Type: replace-cross Abstract: Consider the additive Gaussian model $Y = X + sigma Z$, where $X sim P$ is an unknown signal, $Z sim N(0,1)$ is independent of $X$, and $sigma > 0$ is known. Let $Q$ denote the law of $Y$. We construct a hierarchy of denoisers $T_0, T_1, ldots, T_infty colon mathbb{R} to mathbb{R}$ that depend only on higher-order score functions $q^{(m)}/q$, $m geq 1$, of $Q$ and require no knowledge of the law […]

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In open Federated Learning (FL) environments where no central authority exists, ensuring collaboration fairness relies on decentralized reward settlement, yet the prohibitive cost of permissionless blockchains directly clashes with the high-frequency, iterative nature of model training. Existing solutions either compromise decentralization or suffer from scalability bottlenecks due to linear on-chain costs. To address this, we present SettleFL, a trustless and scalable reward settlement protocol designed to minimize total economic friction by offering a family of two interoperable protocols. […]

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arXiv:2601.20050v1 Announce Type: new Abstract: In this paper we introduce a mixed virtual element method to approximate the solution for the two dimensional generalized Oseen problem. We introduce the pseudostress as an additional unknown, which allows to eliminate the pressure from the system; the pressure can be recovered via a post-process of the pseudostress tensor. We prove existence and uniqueness of the continuous solution via a fixed point argument. Under standard mesh assumptions, we develop a virtual element […]

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Building on top of a Chinese model feels particularly fraught right now.

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I didn’t switch to multi‑vector embeddings because it was trendy. I did it because a single pooled vector kept lying to my search. When you collapse a candidate into one embedding, you’re asking one point in space to simultaneously represent “career arc”, “licenses”, “skills”, and “general profile vibe”. In a recruitment dataset—where a single designation like CFP/CFA can be the gating factor—that pooling turns into a weird kind of blur: the vector is kind of about everything, which […]

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arXiv:2603.02452v1 Announce Type: cross Abstract: A major focus in designing methods for learning distributions defined on manifolds is to alleviate the need to implicitly learn the manifold so that learning can concentrate on the data distribution within the manifold. However, accomplishing this often leads to compute-intensive solutions. In this work, we propose a simple modification to denoising score-matching in the ambient space to implicitly account for the manifold, thereby reducing the burden of learning the manifold while maintaining […]

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I’m looking for hands-on resources (courses, repos, playlists) that actually train agents from pixels, not just theory.I am thinking to buy this course on udemy Advanced AI: Deep Reinforcement Learning in PyTorch (v2). Is there any better free alternative. Anyone experienced guide me on this to go from zero → building autonomous agents? submitted by /u/These_Negotiation936 [link] [comments]

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Existing Graphical User Interface (GUI) agents operate through step-by-step calls to vision language models–taking a screenshot, reasoning about the next action, executing it, then repeating on the new page–resulting in high costs and latency that scale with the number of reasoning steps, and limited accuracy due to no persistent memory of previously visited pages. We propose ActionEngine, a training-free framework that transitions from reactive execution to programmatic planning through a novel two-agent architecture: a Crawling Agent that constructs […]

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arXiv:2601.15478v1 Announce Type: new Abstract: We study multi-agent contract design, where a principal incentivizes a team of agents to take costly actions that jointly determine the project success via a combinatorial reward function. While prior work largely focuses on unconstrained contracts that allow heterogeneous payments across agents, many real-world environments limit payment dispersion. Motivated by this, we study equal-pay contracts, where all agents receive identical payments. Our results also extend to nearly-equal-pay contracts where any two payments are […]

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