Tootfinder

Entropy and Learning of Lipschitz Functions under Log-Concave Measures
Pierre Bizeul, Boaz Klartag
https://arxiv.org/abs/2509.10355 https://arxiv.org/pdf/2…

Entropy and Learning of Lipschitz Functions under Log-Concave Measures
We study regression of $1$-Lipschitz functions under a log-concave measure $μ$ on $\mathbb{R}^d$. We focus on the high-dimensional regime where the sample size $n$ is subexponential in $d$, in which distribution-free estimators are ineffective. We analyze two polynomial-based procedures: the projection estimator, which relies on knowledge of an orthogonal polynomial basis of $μ$, and the least-squares estimator over low-degree polynomials, which requires no knowledge of $μ$ whatsoever. Their…

I do not think that Meta's Metaverse failed cause the devs weren't efficient enough. It's conceptually flawed and underbaked at best, without vision and direction. A toy Mark no longer cares too much about.
(And even getting 5% more efficiency out of LLMs is a stretch, studies show improvement of 1 or 2% at best - because you have to spend a lot of time to clean up the generated mess, especially if you are building frameworks and foundational technologies)

Meta Tells Workers Building Metaverse to Use AI to ‘Go 5x Faster’
Meta says that its coders should be working five times faster and that it expects "a 5x leap in productivity."

A reverse entropy power inequality for i.i.d. log-concave random variables
Zhen Fu, Jiange Li
https://arxiv.org/abs/2510.09206 https://arxiv.org/pdf/2510.0…

A reverse entropy power inequality for i.i.d. log-concave random variables
Let $X$ and $Y$ be independent identically distributed log-concave random variables. We show that $h_\infty(X+Y)-h_\infty(X)$ is maximized when $X$ and $Y$ have exponential distributions. Here, $h_\infty(\cdot)$ is the Rényi entropy of order $\infty$. Analogs for integer-valued log-concave random variables are also obtained.

Prototyping Digital Social Spaces through Metaphor-Driven Design: Translating Spatial Concepts into an Interactive Social Simulation
Yoojin Hong, Martina Di Paola, Braahmi Padmakumar, Hwi Joon Lee, Mahnoor Shafiq, Joseph Seering
https://arxiv.org/abs/2510.02759

Prototyping Digital Social Spaces through Metaphor-Driven Design: Translating Spatial Concepts into an Interactive Social Simulation
Social media platforms are central to communication, yet their designs remain narrowly focused on engagement and scale. While researchers have proposed alternative visions for online spaces, these ideas are difficult to prototype within platform constraints. In this paper, we introduce a metaphor-driven system to help users imagine and explore new social media environments. The system translates users' metaphors into structured sets of platform features and generates interactive simulations pop…

Complex Lies, Real Physics: The Role of Algebra Complexification
Tanguy Marsault (CEA Saclay), Laurent Schoeffel (CEA Saclay)
https://arxiv.org/abs/2509.20929 https://

Complex Lies, Real Physics: The Role of Algebra Complexification
In physics, Lie groups represent the algebraic structure that describes symmetry transformations of a given system. Then, the descending Lie algebra of those groups are necessary real. In most cases, the complexification of those Lie algebra is necessary in order to derive irreductible representations of the Lie algebra and subsequently of the symmetry group. In this paper, we give a precise definition of the concept and prove step by step an important result $$\left(\mathfrak{g}^\mathbb{R}\rig…

SENSE models: an open source solution for multilingual and multimodal semantic-based tasks
Salima Mdhaffar, Haroun Elleuch, Chaimae Chellaf, Ha Nguyen, Yannick Est\`eve
https://arxiv.org/abs/2509.12093

SENSE models: an open source solution for multilingual and multimodal semantic-based tasks
This paper introduces SENSE (Shared Embedding for N-lingual Speech and tExt), an open-source solution inspired by the SAMU-XLSR framework and conceptually similar to Meta AI's SONAR models. These approaches rely on a teacher-student framework to align a self-supervised speech encoder with the language-agnostic continuous representations of a text encoder at the utterance level. We describe how the original SAMU-XLSR method has been updated by selecting a stronger teacher text model and a better…

A Tauberian approach to metric scaling limits of random discrete structures, with an application to random planar maps
William Fleurat
https://arxiv.org/abs/2510.05078 https://

A Tauberian approach to metric scaling limits of random discrete structures, with an application to random planar maps
We prove sandwich theorems and a Tauberian theorem in the space of compact metric measure spaces, endowed with the Gromov-Hausdorff-Prokhorov (GHP) topology. These results hold with respect to a close relative of Gromov's Lipschitz order. As a proof-of-concept of a general method to prove metric scaling limits of random discrete structures, we give an application to the theory of random planar maps: the Brownian sphere is the scaling limit in the GHP topology of irreducible quandrangulations. O…

A Preliminary Study: Pathwise Patching and the Geometric Nature of Quasi-Sure Existence in GSDEs
Guangqian Zhao
https://arxiv.org/abs/2510.06054 https://ar…

A Preliminary Study: Pathwise Patching and the Geometric Nature of Quasi-Sure Existence in GSDEs
This paper introduces a preliminary working perspective on constructing solutions to G-stochastic differential equations (GSDEs). We propose a pathwise patching methodology that offers a geometric interpretation for the concept of quasi-sure solutions. Unlike conventional methods based on fixed-point theorems in function spaces (which secure uniqueness in the quasi-sure sense), our approach focuses on defining the solution $X_t$ directly on the path space by synthesizing individual solutions $X…

Where Do I 'Add the Egg'?: Exploring Agency and Ownership in AI Creative Co-Writing Systems
Dashiel Carrera, Jeb Thomas-Mitchell, Daniel Wigdor
https://arxiv.org/abs/2509.15440

Where Do I 'Add the Egg'?: Exploring Agency and Ownership in AI Creative Co-Writing Systems
AI co-writing systems challenge long held ideals about agency and ownership in the creative process, thereby hindering widespread adoption. In order to address this, we investigate conceptions of agency and ownership in AI creative co-writing. Drawing on insights from a review of commercial systems, we developed three co-writing systems with identical functionality but distinct interface metaphors: agentic, tool-like, and magical. Through interviews with professional and non-professional writer…

Contractive kinetic Langevin samplers beyond global Lipschitz continuity
Iosif Lytras, Panagiotis Mertikopoulos
https://arxiv.org/abs/2509.12031 https://ar…

Contractive kinetic Langevin samplers beyond global Lipschitz continuity
In this paper, we examine the problem of sampling from log-concave distributions with (possibly) superlinear gradient growth under kinetic (underdamped) Langevin algorithms. Using a carefully tailored taming scheme, we propose two novel discretizations of the kinetic Langevin SDE, and we show that they are both contractive and satisfy a log-Sobolev inequality. Building on this, we establish a series of non-asymptotic bounds in $2$-Wasserstein distance between the law reached by each algorithm a…