Tootfinder

Measuring and Predicting Where and When Pathologists Focus their Visual Attention while Grading Whole Slide Images of Cancer
Souradeep Chakraborty, Ruoyu Xue, Rajarsi Gupta, Oksana Yaskiv, Constantin Friedman, Natallia Sheuka, Dana Perez, Paul Friedman, Won-Tak Choi, Waqas Mahmud, Beatrice Knudsen, Gregory Zelinsky, Joel Saltz, Dimitris Samaras
https://

Measuring and Predicting Where and When Pathologists Focus their Visual Attention while Grading Whole Slide Images of Cancer
The ability to predict the attention of expert pathologists could lead to decision support systems for better pathology training. We developed methods to predict the spatio-temporal (where and when) movements of pathologists' attention as they grade whole slide images (WSIs) of prostate cancer. We characterize a pathologist's attention trajectory by their x, y, and m (magnification) movements of a viewport as they navigate WSIs using a digital microscope. This information was obtained from 43 p…

BitsAI-Fix: LLM-Driven Approach for Automated Lint Error Resolution in Practice
Yuanpeng Li, Qi Long, Zhiyuan Yao, Jian Xu, Lintao Xie, Xu He, Lu Geng, Xin Han, Yueyan Chen, Wenbo Duan
https://arxiv.org/abs/2508.03487

BitsAI-Fix: LLM-Driven Approach for Automated Lint Error Resolution in Practice
As enterprise codebases continue to grow in scale and complexity, the volume of lint errors far exceeds engineers' manual remediation capacity, leading to continuous accumulation of technical debt and hindered development efficiency. This paper presents BitsAI-Fix, an automated lint error remediation workflow based on Large Language Models (LLMs), designed to address this critical challenge in industrial-scale environments. BitsAI-Fix employs tree-sitter for context expansion and generates sear…

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models
Haoyue Tan, Yu Li, Zhenxi Zhang, Xiaoran Shi, Feng Zhou
https://arxiv.org/abs/2508.01719 htt…

ModFus-DM: Explore the Representation in Modulated Signal Diffusion Generated Models
Automatic modulation classification (AMC) is essential for wireless communication systems in both military and civilian applications. However, existing deep learning-based AMC methods often require large labeled signals and struggle with non-fixed signal lengths, distribution shifts, and limited labeled signals. To address these challenges, we propose a modulation-driven feature fusion via diffusion model (ModFus-DM), a novel unsupervised AMC framework that leverages the generative capacity of …

Nützliches Feature: AirPods und Beats-Stöpsel legen sich schlafen
Mit iOS 26 kann man festlegen, dass verschiedene beliebte Ohrhörer von Apple und Beats erkennen, wenn man einpennt. Dann geht es automatisch auf Pause.

SlotMatch: Distilling Temporally Consistent Object-Centric Representations for Unsupervised Video Segmentation
Diana-Nicoleta Grigore, Neelu Madan, Andreas Mogelmose, Thomas B. Moeslund, Radu Tudor Ionescu
https://arxiv.org/abs/2508.03411

SlotMatch: Distilling Temporally Consistent Object-Centric Representations for Unsupervised Video Segmentation
Unsupervised video segmentation is a challenging computer vision task, especially due to the lack of supervisory signals coupled with the complexity of visual scenes. To overcome this challenge, state-of-the-art models based on slot attention often have to rely on large and computationally expensive neural architectures. To this end, we propose a simple knowledge distillation framework that effectively transfers object-centric representations to a lightweight student. The proposed framework, ca…

This https://arxiv.org/abs/2502.14879 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_eco…

Limited attention and models of choice: A behavioral equivalence
We show that many models of choice can be alternatively represented as special cases of choice with limited attention (Masatlioglu, Nakajima, and Ozbay, 2012), singling out the properties of the unobserved attention filters that explain the observed choices.For each specification, information about the DM's consideration sets and preference is inferred from violations of the contraction consistency axiom, and it is compared with the welfare indications obtained from equivalent models. Remarkabl…

Attenuation of the ultra-high-energy neutrino flux by dark matter scatterings
Ivan Esteban, Alejandro Ibarra
https://arxiv.org/abs/2508.02869 https://arxiv…

Attenuation of the ultra-high-energy neutrino flux by dark matter scatterings
A flux of ultra-high-energy (UHE) neutrinos is generally expected to be produced by astrophysical sources at cosmological distances and to reach Earth. In this paper, we investigate the impact of neutrino scattering with dark matter (DM) particles in both the intergalactic medium and the Milky Way on the total flux, energy spectrum, and arrival directions of UHE neutrinos. We emphasize the complementarity of neutrino detectors at different latitudes to probe the anisotropy in the flux at Earth …

I just used recursive routing on my @… to automatically switch to using a USB 4g dongle when the main fiber connection goes down.
I'm a networking GOD i say!
Not really, but this is very cool. My work vpn does not even need to be restarted, this is awesome!

MetaScope: Optics-Driven Neural Network for Ultra-Micro Metalens Endoscopy
Wuyang Li, Wentao Pan, Xiaoyuan Liu, Zhendong Luo, Chenxin Li, Hengyu Liu, Din Ping Tsai, Mu Ku Chen, Yixuan Yuan
https://arxiv.org/abs/2508.03596

MetaScope: Optics-Driven Neural Network for Ultra-Micro Metalens Endoscopy
Miniaturized endoscopy has advanced accurate visual perception within the human body. Prevailing research remains limited to conventional cameras employing convex lenses, where the physical constraints with millimetre-scale thickness impose serious impediments on the micro-level clinical. Recently, with the emergence of meta-optics, ultra-micro imaging based on metalenses (micron-scale) has garnered great attention, serving as a promising solution. However, due to the physical difference of met…

Automated Mechanism to Support Trade Transactions in Smart Contracts with Upgrade and Repair
Christian Gang Liu, Peter Bodorik, Dawn Jutla
https://arxiv.org/abs/2506.03877

Automated Mechanism to Support Trade Transactions in Smart Contracts with Upgrade and Repair
In our previous research, we addressed the problem of automated transformation of models, represented using the business process model and notation (BPMN) standard, into the methods of a smart contract. The transformation supports BPMN models that contain complex multi-step activities that are supported using our concept of multi-step nested trade transactions, wherein the transactional properties are enforced by a mechanism generated automatically by the transformation process from a BPMN mode…