Tootfinder

Plug-and-Play Latent Diffusion for Electromagnetic Inverse Scattering with Application to Brain Imaging
Rui Guo, Yi Zhang, Yhonatan Kvich, Tianyao Huang, Maokun Li, Yonina C. Eldar
https://arxiv.org/abs/2509.04860

Plug-and-Play Latent Diffusion for Electromagnetic Inverse Scattering with Application to Brain Imaging
Electromagnetic (EM) imaging is an important tool for non-invasive sensing with low-cost and portable devices. One emerging application is EM stroke imaging, which enables early diagnosis and continuous monitoring of brain strokes. Quantitative imaging is achieved by solving an inverse scattering problem (ISP) that reconstructs permittivity and conductivity maps from measurements. In general, the reconstruction accuracy is limited by its inherent nonlinearity and ill-posedness. Existing methods…

LETToT: Label-Free Evaluation of Large Language Models On Tourism Using Expert Tree-of-Thought
Ruiyan Qi, Congding Wen, Weibo Zhou, Shangsong Liang, Lingbo Li
https://arxiv.org/abs/2508.11280

LETToT: Label-Free Evaluation of Large Language Models On Tourism Using Expert Tree-of-Thought
Evaluating large language models (LLMs) in specific domain like tourism remains challenging due to the prohibitive cost of annotated benchmarks and persistent issues like hallucinations. We propose $\textbf{L}$able-Free $\textbf{E}$valuation of LLM on $\textbf{T}$ourism using Expert $\textbf{T}$ree-$\textbf{o}$f-$\textbf{T}$hought (LETToT), a framework that leverages expert-derived reasoning structures-instead of labeled data-to access LLMs in tourism. First, we iteratively refine and validate …