Tootfinder

Aurora as seen from Florida

Moody Urbanity - UP ⬆️
情绪化城市 - 上面 ⬆️
📷 Nikon FE
🎞️ Ilford HP5 Plus 400, expired 1993
#filmphotography #Photography #blackandwhite

Motion of Elastic Thin Films by Evaporation-Condensation in the Dewetting Regime
M. S. Indulekha
https://arxiv.org/abs/2508.07562 https://arxiv.org/pdf/250…

Motion of Elastic Thin Films by Evaporation-Condensation in the Dewetting Regime
In this work, we show the short-time existence of solutions of the evolution equations that represent the solid state dewetting of thin films through evaporation-condensation as a two dimensional sharp interface variational model. The evolution law is established as the $L^2$ gradient flow of surface energies in the presence of epitaxial strain. The main novelty is the presence of moving contact lines when the film formation is governed by the evaporation-condensation method.

'Thank you, Jerry!' Packers fans mock Cowboys owner as Micah Parsons looks ahead to Week 4 game in Dallas

https://www.cbssports.com/nfl/news/thank-y

Towards Adaptive ML Benchmarks: Web-Agent-Driven Construction, Domain Expansion, and Metric Optimization
Hangyi Jia, Yuxi Qian, Hanwen Tong, Xinhui Wu, Lin Chen, Feng Wei
https://arxiv.org/abs/2509.09321

Towards Adaptive ML Benchmarks: Web-Agent-Driven Construction, Domain Expansion, and Metric Optimization
Recent advances in large language models (LLMs) have enabled the emergence of general-purpose agents for automating end-to-end machine learning (ML) workflows, including data analysis, feature engineering, model training, and competition solving. However, existing benchmarks remain limited in task coverage, domain diversity, difficulty modeling, and evaluation rigor, failing to capture the full capabilities of such agents in realistic settings. We present TAM Bench, a diverse, realistic, and st…

Taming Spontaneous Stop-and-Go Traffic Waves: A Bifurcation Perspective of A Dynamical Map
Suzhou Huang, Jian Hu
https://arxiv.org/abs/2509.09466 https://a…

Taming Spontaneous Stop-and-Go Traffic Waves: A Bifurcation Perspective of A Dynamical Map
We consider a discrete-time dynamical system in a car-following context. The system was recently introduced to parsimoniously model human driving behavior based on utility maximization. The parameters of the model were calibrated using vehicle trajectory data from the Sugiyama experiment. It was shown that such a system can accurately reproduce the observed collective phenomena of a more elaborate experiment by Tadaki et al. Once the heterogeneity and noise are switched off, the model defines a…

On The Road - To Xi’An/Urban Tomb 🪦
在路上 - 去西安/城市坟茔 🪦
📷 Pentax MX
🎞️Lucky SHD 400
#filmphotography #Photography #blackandwhite

Sandwich Construction of Symmetry TFTs for the Centre Symmetries of Chern-Simons, Yang-Mills, and Einstein Gravity
Leron Borsten, Dimitri Kanakaris, Hyungrok Kim
https://arxiv.org/abs/2509.08819

Sandwich Construction of Symmetry TFTs for the Centre Symmetries of Chern-Simons, Yang-Mills, and Einstein Gravity
We construct symmetry topological field theories (SymTFTs) using the sandwich construction of Pulmann-Ševera-Valach that manifest the centre symmetries of Chern-Simons theory and Yang-Mills theory as well as general relativity in the MacDowell-Mansouri formulation. The 'filling' of the sandwich is an AKSZ sigma model whose target space is a Weil algebra, augmented with discrete degrees of freedom given by a choice of topological boundary condition.

PAC Learnability in the Presence of Performativity
Ivan Kirev, Lyuben Baltadzhiev, Nikola Konstantinov
https://arxiv.org/abs/2510.08335 https://arxiv.org/p…

PAC Learnability in the Presence of Performativity
Following the wide-spread adoption of machine learning models in real-world applications, the phenomenon of performativity, i.e. model-dependent shifts in the test distribution, becomes increasingly prevalent. Unfortunately, since models are usually trained solely based on samples from the original (unshifted) distribution, this performative shift may lead to decreased test-time performance. In this paper, we study the question of whether and when performative binary classification problems are…

R-Horizon: How Far Can Your Large Reasoning Model Really Go in Breadth and Depth?
Yi Lu, Jianing Wang, Linsen Guo, Wei He, Hongyin Tang, Tao Gui, Xuanjing Huang, Xuezhi Cao, Wei Wang, Xunliang Cai
https://arxiv.org/abs/2510.08189

R-Horizon: How Far Can Your Large Reasoning Model Really Go in Breadth and Depth?
Recent trends in test-time scaling for reasoning models (e.g., OpenAI o1, DeepSeek-R1) have led to remarkable improvements through long Chain-of-Thought (CoT). However, existing benchmarks mainly focus on immediate, single-horizon tasks, failing to adequately evaluate models' ability to understand and respond to complex, long-horizon scenarios. To address this incomplete evaluation of Large Reasoning Models (LRMs), we propose R-HORIZON, a method designed to stimulate long-horizon reasoning beha…