Tootfinder

On Kotzig's conjecture in random graphs
Stefan Glock, Amedeo Sgueglia
https://arxiv.org/abs/2510.01949 https://arxiv.org/pdf/2510.01949

On Kotzig's conjecture in random graphs
In 1963, Anton Kotzig famously conjectured that $K_{n}$, the complete graph of order $n$, where $n$ is even, can be decomposed into $n-1$ perfect matchings such that every pair of these matchings forms a Hamilton cycle. The problem is still wide open and here we consider a variant of it for the binomial random graph $G(n,p)$. We prove that, for every fixed $k$, there exists a constant $C=C(k)$ such that, when $p\ge \frac{C \log n}{n}$, with high probability, $G(n,p)$ contains $k$ edge-disjoint …

Learning to Look at the Other Side: A Semantic Probing Study of Word Embeddings in LLMs with Enabled Bidirectional Attention
Zhaoxin Feng, Jianfei Ma, Emmanuele Chersoni, Xiaojing Zhao, Xiaoyi Bao
https://arxiv.org/abs/2510.01652

Learning to Look at the Other Side: A Semantic Probing Study of Word Embeddings in LLMs with Enabled Bidirectional Attention
Autoregressive Large Language Models (LLMs) demonstrate exceptional performance in language understanding and generation. However, their application in text embedding tasks has been relatively slow, along with the analysis of their semantic representation in probing tasks, due to the constraints of the unidirectional attention mechanism. This paper aims to explore whether such constraints can be overcome by enabling bidirectional attention in LLMs. We tested different variants of the Llama ar…

Adaptive Learning Strategies for Mitotic Figure Classification in MIDOG2025 Challenge
Biwen Meng, Xi Long, Jingxin Liu
https://arxiv.org/abs/2509.02640 https://

Adaptive Learning Strategies for Mitotic Figure Classification in MIDOG2025 Challenge
Atypical mitotic figures (AMFs) are clinically relevant indicators of abnormal cell division, yet their reliable detection remains challenging due to morphological ambiguity and scanner variability. In this work, we investigated three variants of adapting the pathology foundation model UNI2-h for the MIDOG2025 Track 2 challenge. Starting from a LoRA-based baseline, we found that visual prompt tuning (VPT) substantially improved generalization, and that further integrating test-time augmentation…

The log-Sobolev inequality and correlation functions for the renormalization of 1D Ising model
Kaiyuan Cui, Fuzhou Gong
https://arxiv.org/abs/2510.01950 https://

The log-Sobolev inequality and correlation functions for the renormalization of 1D Ising model
The renormalization group (RG) method is an important tool for studying critical phenomena. In this paper, we employ stochastic analysis techniques to investigate the stochastic partial differential equation (SPDE) derived by regularizing and continuousizing the discrete stochastic equation, which is a variant of stochastic quantization equation of the one dimensional (1D) Ising model. Firstly, we give the regularity estimates for the solution to SPDE. Secondly, we prove the Clark-Ocone-Haussma…

An existence theorem for sliding minimal sets
Guy David, Camille Labourie
https://arxiv.org/abs/2510.01905 https://arxiv.org/pdf/2510.01905

An existence theorem for sliding minimal sets
We prove an existence theorem for the sliding boundary variant of the Plateau problem for $2$-dimensional sets in $\mathbb{R}^n$. The simplest case of sufficient condition is when $n=3$ and the boundary $Γ$ is a finite disjoint union of smooth closed curves contained in the boundary of a convex body, but the main point of our sufficient condition is to prevent the limits in measure of a minimizing sequence to have singularities of type $\mathbb{Y}$ along $Γ$.

Evaluating New AI Cell Foundation Models on Challenging Kidney Pathology Cases Unaddressed by Previous Foundation Models
Runchen Wang, Junlin Guo, Siqi Lu, Ruining Deng, Zhengyi Lu, Yanfan Zhu, Yuechen Yang, Chongyu Qu, Yu Wang, Shilin Zhao, Catie Chang, Mitchell Wilkes, Mengmeng Yin, Haichun Yang, Yuankai Huo
https://arxiv.org/abs/2510.01…

Evaluating New AI Cell Foundation Models on Challenging Kidney Pathology Cases Unaddressed by Previous Foundation Models
Accurate cell nuclei segmentation is critical for downstream tasks in kidney pathology and remains a major challenge due to the morphological diversity and imaging variability of renal tissues. While our prior work has evaluated early-generation AI cell foundation models in this domain, the effectiveness of recent cell foundation models remains unclear. In this study, we benchmark advanced AI cell foundation models (2025), including CellViT++ variants and Cellpose-SAM, against three widely used…

From Behavioral Performance to Internal Competence: Interpreting Vision-Language Models with VLM-Lens
Hala Sheta, Eric Huang, Shuyu Wu, Ilia Alenabi, Jiajun Hong, Ryker Lin, Ruoxi Ning, Daniel Wei, Jialin Yang, Jiawei Zhou, Ziqiao Ma, Freda Shi
https://arxiv.org/abs/2510.02292

From Behavioral Performance to Internal Competence: Interpreting Vision-Language Models with VLM-Lens
We introduce VLM-Lens, a toolkit designed to enable systematic benchmarking, analysis, and interpretation of vision-language models (VLMs) by supporting the extraction of intermediate outputs from any layer during the forward pass of open-source VLMs. VLM-Lens provides a unified, YAML-configurable interface that abstracts away model-specific complexities and supports user-friendly operation across diverse VLMs. It currently supports 16 state-of-the-art base VLMs and their over 30 variants, and …

Origin of nucleon mass in the light of PSR J0614-3329 with quark-hadron crossover
Bikai Gao, Yuk-Kei Kong, Yong-Liang Ma
https://arxiv.org/abs/2509.03008 https://

Origin of nucleon mass in the light of PSR J0614-3329 with quark-hadron crossover
The recent NICER observation of PSR J0614-3329, revealing the smallest reliably measured neutron star radius of $R = 10.29^{+1.01}_{-0.86}$ km at mass $M = 1.44^{+0.06}_{-0.07} M_\odot$, provides an unprecedented constraint on the equation of state of dense matter. We investigate the implications of this measurement for the origin of nucleon mass within the parity doublet model framework, which naturally incorporates both chiral variant and chiral invariant mass components. We construct unified…

A Model-Based Extended State Observer for Discrete-Time Linear Multivariable Systems
Jinfeng Chen, Zhiqiang Gao, Qin Lin
https://arxiv.org/abs/2510.01007 https://

A Model-Based Extended State Observer for Discrete-Time Linear Multivariable Systems
A model-based extended state observer (MB-ESO) and its variant are proposed for discrete-time linear multivariable systems, where multiple disturbances are defined as an extended state vector in the same manner as in the original formulation of ESO. The variant MB-ESO extends the MB-ESO to address cases where the disturbance gain matrix is non-diagonal. Leveraging the connection between the variant MB-ESO and the well-known unknown input observer (UIO), the condition for the existence of a MB-E…

Analyzing Dialectical Biases in LLMs for Knowledge and Reasoning Benchmarks
Eileen Pan, Anna Seo Gyeong Choi, Maartje ter Hoeve, Skyler Seto, Allison Koenecke
https://arxiv.org/abs/2510.00962

Analyzing Dialectical Biases in LLMs for Knowledge and Reasoning Benchmarks
Large language models (LLMs) are ubiquitous in modern day natural language processing. However, previous work has shown degraded LLM performance for under-represented English dialects. We analyze the effects of typifying "standard" American English language questions as non-"standard" dialectal variants on multiple choice question answering tasks and find up to a 20% reduction in accuracy. Additionally, we investigate the grammatical basis of under-performance in non-"standard" English question…