Tootfinder

An improved bound for strongly regular graphs with smallest eigenvalue $-m$
Jack Koolen, Chenhui Lv, Greg Markowsky, Jongyook Park
https://arxiv.org/abs/2506.04964

An improved bound for strongly regular graphs with smallest eigenvalue $-m$
In 1979, Neumaier gave a bound on $λ$ in terms of $m$ and $μ$, where $-m$ is the smallest eigenvalue of a primitive strongly regular graph, unless the graph in question belongs to one of the two infinite families of strongly regular graphs. We improve this result. We also indicate how our methods can be used to give an alternate derivation of Bruck's Completion Theorem for orthogonal arrays.

Identifying actionable driver mutations in lung cancer using an efficient Asymmetric Transformer Decoder
Biagio Brattoli, Jack Shi, Jongchan Park, Taebum Lee, Donggeun Yoo, Sergio Pereira
https://arxiv.org/abs/2508.02431

Identifying actionable driver mutations in lung cancer using an efficient Asymmetric Transformer Decoder
Identifying actionable driver mutations in non-small cell lung cancer (NSCLC) can impact treatment decisions and significantly improve patient outcomes. Despite guideline recommendations, broader adoption of genetic testing remains challenging due to limited availability and lengthy turnaround times. Machine Learning (ML) methods for Computational Pathology (CPath) offer a potential solution; however, research often focuses on only one or two common mutations, limiting the clinical value of the…