Tootfinder

Hiding in Plain Sight: Query Obfuscation via Random Multilingual Searches
Anton Firc, Jan Klus\'a\v{c}ek, Kamil Malinka
https://arxiv.org/abs/2506.04963

Hiding in Plain Sight: Query Obfuscation via Random Multilingual Searches
Modern search engines extensively personalize results by building detailed user profiles based on query history and behaviour. While personalization can enhance relevance, it introduces privacy risks and can lead to filter bubbles. This paper proposes and evaluates a lightweight, client-side query obfuscation strategy using randomly generated multilingual search queries to disrupt user profiling. Through controlled experiments on the Seznam.cz search engine, we assess the impact of interleaving…

Experimental and simulative study on laser irradiation of 3D-printed micro-structures at intensities relevant for inertial confinement fusion
M. Cipriani, F. Consoli, M. Scisci\`o, A. Solovjovas, I. A. Petsi, M. Malinauskas, P. Andreoli, G. Cristofari, E. Di Ferdinando, G. Di Giorgio
https://arxiv.org/abs/2506.04017

Experimental and simulative study on laser irradiation of 3D-printed micro-structures at intensities relevant for inertial confinement fusion
Inertial confinement fusion requires a constant search for the most effective materials for improving the efficiency of the compression of the capsule and of the laser-to-target energy transfer. Foams could provide a solution to these problems, but they require further experimental and theoretical investigation. The new 3D-printing technologies, such as the two-photon polymerization, are opening a new era in the production of foams, allowing for the fine control of the material morphology. Deta…

This https://arxiv.org/abs/2505.03071 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

The Search for Squawk: Agile Modeling in Bioacoustics
Passive acoustic monitoring (PAM) has shown great promise in helping ecologists understand the health of animal populations and ecosystems. However, extracting insights from millions of hours of audio recordings requires the development of specialized recognizers. This is typically a challenging task, necessitating large amounts of training data and machine learning expertise. In this work, we introduce a general, scalable and data-efficient system for developing recognizers for novel bioacoust…