Tootfinder

AutoIntent: AutoML for Text Classification
Ilya Alekseev, Roman Solomatin, Darina Rustamova, Denis Kuznetsov
https://arxiv.org/abs/2509.21138 https://arxiv…

AutoIntent: AutoML for Text Classification
AutoIntent is an automated machine learning tool for text classification tasks. Unlike existing solutions, AutoIntent offers end-to-end automation with embedding model selection, classifier optimization, and decision threshold tuning, all within a modular, sklearn-like interface. The framework is designed to support multi-label classification and out-of-scope detection. AutoIntent demonstrates superior performance compared to existing AutoML tools on standard intent classification datasets and …

Symmetry-breaking bifurcation of periodic solutions for a free-boundary tumor model
Wenhua He, Mingxin Wang, Ruixiang Xing
https://arxiv.org/abs/2508.19954 https://

Symmetry-breaking bifurcation of periodic solutions for a free-boundary tumor model
In this paper, we consider a free boundary multi-layer tumor model that incorporates a $T-$periodic provision of external nutrients $Φ(t)$. The simplified model contains three parameters: the mean of periodic external nutrients $Φ(t)$, the threshold concentration $\widetildeσ$ for proliferation and the cell to cell adhesiveness coefficient $γ$. We first study the flat solution and give a complete classification about $\frac{1}{T} \int_0^T Φ(t) d t$ and $\widetildeσ$ according to global st…

Improving Decision Trees through the Lens of Parameterized Local Search
Juha Harviainen, Frank Sommer, Manuel Sorge
https://arxiv.org/abs/2510.12726 https://

Improving Decision Trees through the Lens of Parameterized Local Search
Algorithms for learning decision trees often include heuristic local-search operations such as (1) adjusting the threshold of a cut or (2) also exchanging the feature of that cut. We study minimizing the number of classification errors by performing a fixed number of a single type of these operations. Although we discover that the corresponding problems are NP-complete in general, we provide a comprehensive parameterized-complexity analysis with the aim of determining those properties of the pr…