Tootfinder

FreeBSD provides the standard KDE Plasma package, which is the preferred way as recommended by KDE themselves. Nevertheless, you can still uninstall i.e. Discover and Konqueror, which are part of that base package (like I do).
Don't be put off by the inclusion of kde-base-apps in your removal overview, only the relevant parts for that application will be removed. All other apps and libraries will stay put and continue to work.

ScoreHOI: Physically Plausible Reconstruction of Human-Object Interaction via Score-Guided Diffusion
Ao Li, Jinpeng Liu, Yixuan Zhu, Yansong Tang
https://arxiv.org/abs/2509.07920

ScoreHOI: Physically Plausible Reconstruction of Human-Object Interaction via Score-Guided Diffusion
Joint reconstruction of human-object interaction marks a significant milestone in comprehending the intricate interrelations between humans and their surrounding environment. Nevertheless, previous optimization methods often struggle to achieve physically plausible reconstruction results due to the lack of prior knowledge about human-object interactions. In this paper, we introduce ScoreHOI, an effective diffusion-based optimizer that introduces diffusion priors for the precise recovery of huma…

Water Demand Forecasting of District Metered Areas through Learned Consumer Representations
Adithya Ramachandran, Thorkil Flensmark B. Neergaard, Tom\'as Arias-Vergara, Andreas Maier, Siming Bayer
https://arxiv.org/abs/2509.07515

Water Demand Forecasting of District Metered Areas through Learned Consumer Representations
Advancements in smart metering technologies have significantly improved the ability to monitor and manage water utilities. In the context of increasing uncertainty due to climate change, securing water resources and supply has emerged as an urgent global issue with extensive socioeconomic ramifications. Hourly consumption data from end-users have yielded substantial insights for projecting demand across regions characterized by diverse consumption patterns. Nevertheless, the prediction of water…

A "good regulator theorem" for embodied agents
Nathaniel Virgo, Martin Biehl, Manuel Baltieri, Matteo Capucci
https://arxiv.org/abs/2508.06326 https://

A "good regulator theorem" for embodied agents
In a classic paper, Conant and Ashby claimed that "every good regulator of a system must be a model of that system." Artificial Life has produced many examples of systems that perform tasks with apparently no model in sight; these suggest Conant and Ashby's theorem doesn't easily generalise beyond its restricted setup. Nevertheless, here we show that a similar intuition can be fleshed out in a different way: whenever an agent is able to perform a regulation task, it is possible for an observer …

Simulating sparse SYK model with a randomized algorithm on a trapped-ion quantum computer
Etienne Granet, Yuta Kikuchi, Henrik Dreyer, Enrico Rinaldi
https://arxiv.org/abs/2507.07530

Simulating sparse SYK model with a randomized algorithm on a trapped-ion quantum computer
The Sachdev-Ye-Kitaev (SYK) model describes a strongly correlated quantum system that shows a strong signature of quantum chaos. Due to its chaotic nature, the simulation of real-time dynamics becomes quickly intractable by means of classical numerics, and thus, quantum simulation is deemed to be an attractive alternative. Nevertheless, quantum simulations of the SYK model on noisy quantum processors are severely limited by the complexity of its Hamiltonian. In this work, we simulate the real-t…

ASLSL: Adaptive shared latent structure learning with incomplete multi-modal physiological data for multi-dimensional emotional feature selection
Xueyuan Xu, Tianze Yu, Wenjia Dong, Fulin Wei, Li Zhuo
https://arxiv.org/abs/2508.05934

ASLSL: Adaptive shared latent structure learning with incomplete multi-modal physiological data for multi-dimensional emotional feature selection
Recently, multi-modal physiological signals based emotion recognition has garnered increasing attention in the field of brain-computer interfaces. Nevertheness, the associated multi-modal physiological features are often high-dimensional and inevitably include irrelevant, redundant, and noisy representation, which can easily lead to overfitting, poor performance, and high computational complexity in emotion classifiers. Feature selection has been widely applied to address these challenges. Howe…

Cosmological phase transitions without high-temperature expansions
Pablo Navarrete, Risto Paatelainen, Kaapo Sepp\"anen, Tuomas V. I. Tenkanen
https://arxiv.org/abs/2507.07014

Cosmological phase transitions without high-temperature expansions
We introduce a new framework for perturbatively computing equilibrium thermodynamic properties of cosmological phase transitions to high loop orders, using the full four-dimensional resummed thermal effective potential and avoiding the limitations of standard high-temperature approximations. By systematically disentangling the physics of hard and soft momentum scales, our approach unifies their treatment within a single expression, enabling consistent handling of both vacuum and thermal diverge…

LightSwitch: Multi-view Relighting with Material-guided Diffusion
Yehonathan Litman, Fernando De la Torre, Shubham Tulsiani
https://arxiv.org/abs/2508.06494 https://

LightSwitch: Multi-view Relighting with Material-guided Diffusion
Recent approaches for 3D relighting have shown promise in integrating 2D image relighting generative priors to alter the appearance of a 3D representation while preserving the underlying structure. Nevertheless, generative priors used for 2D relighting that directly relight from an input image do not take advantage of intrinsic properties of the subject that can be inferred or cannot consider multi-view data at scale, leading to subpar relighting. In this paper, we propose Lightswitch, a novel …

Layer Cake Representations for Quantum Divergences
Po-Chieh Liu, Christoph Hirche, Hao-Chung Cheng
https://arxiv.org/abs/2507.07065 https://

Layer Cake Representations for Quantum Divergences
Defining suitable quantum extensions of classical divergences often poses a challenge due to the non-commutative nature of quantum information. In this work, we propose a new approach via what we call the layer cake representation. The resulting quantum Rényi and $f$-divergences are then proven to be equivalent to those recently defined via integral representations. Nevertheless, the approach can provide several insights. We give an alternative proof of the integral representation of the relat…

Low-energy theory of jet processes and PDF factorization
Thomas Becher, Patrick Hager, Sebastian Jaskiewicz, Matthias Neubert, Dominik Schwienbacher
https://arxiv.org/abs/2509.07082

Low-energy theory of jet processes and PDF factorization
The consistency of collinear factorization violation with PDF factorization has been an outstanding challenge and subject of considerable debate. In this work we demonstrate their compatibility using a factorization theorem for non-global jet observables. Our analysis relies on consistency relations derived from renormalization conditions in effective field theory. We verify these relations through an explicit computation at three-loop order and show that the double-logarithmic evolution sourci…