Tootfinder

Gravity versus astrophysics in black hole images and photon rings: equatorial emissions and spherically symmetric spacetimes
I. Urso, F. H. Vincent, M. Wielgus, T. Paumard, G. Perrin
https://arxiv.org/abs/2506.13482

Gravity versus astrophysics in black hole images and photon rings: equatorial emissions and spherically symmetric spacetimes
The EHT collaboration released in 2019 the first horizon-scale images of a black hole accretion flow, opening a novel route for plasma physics comprehension and gravitational tests. Although the present unresolved images deeply depend on the astrophysical properties of the accreted matter, GR predicts that they contain highly lensed observables, the "photon rings", embodying the effects of strong-field gravity. Focusing on the supermassive black hole M87* and adopting a geometrically thin, equa…

Datenschutz: Tätigkeitsberichte verdeutlichen Sorgen um KI-Überwachungspraktiken
Die Landesdatenschützerinnen von NRW und Berlin sprechen sich anlässlich ihrer Tätigkeitsberichte gegen Überwachungspraktiken aus, die auf dem Vormarsch sind.

Happy #PrideMonth! 🏳️‍⚧️🏳️‍🌈
I’m just too fabulously queer and genderfluid to function like anyone expects. My identity is a whole spectrum, shifting and sparkling with every color and every gender. 🌈✨
Some days I’m femme, some days I’m masc, and some days I’m something totally unique and undefined. 💖💙🤍
My

Optimal Non-Adaptive Group Testing with One-Sided Error Guarantees
Daniel McMorrow, Jonathan Scarlett
https://arxiv.org/abs/2506.10374 https://

Optimal Non-Adaptive Group Testing with One-Sided Error Guarantees
The group testing problem consists of determining a sparse subset of defective items from within a larger set of items via a series of tests, where each test outcome indicates whether at least one defective item is included in the test. We study the approximate recovery setting, where the recovery criterion of the defective set is relaxed to allow a small number of items to be misclassified. In particular, we consider one-sided approximate recovery criteria, where we allow either only false neg…

This https://arxiv.org/abs/2505.19193 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

Interpretable Graph Learning Over Sets of Temporally-Sparse Data
Real-world medical data often includes measurements from multiple signals that are collected at irregular and asynchronous time intervals. For example, different types of blood tests can be measured at different times and frequencies, resulting in fragmented and unevenly scattered temporal data. Similar issues of irregular sampling of different attributes occur in other domains, such as monitoring of large systems using event log files or the spread of fake news on social networks. Effectively …

User Altruism in Recommendation Systems
Ekaterina Fedorova, Madeline Kitch, Chara Podimata
https://arxiv.org/abs/2506.04525 https://a…

User Altruism in Recommendation Systems
Users of social media platforms based on recommendation systems (RecSys) (e.g. TikTok, X, YouTube) strategically interact with platform content to influence future recommendations. On some such platforms, users have been documented to form large-scale grassroots movements encouraging others to purposefully interact with algorithmically suppressed content in order to "boost" its recommendation; we term this behavior user altruism. To capture this behavior, we study a game between users and a Rec…

This https://arxiv.org/abs/2412.17831 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

High-resolution urban air pollution and thermal comfort mapping: an application of drive mobile sensing platform for smart city services
Air pollutant exposure exhibits significant spatial and temporal variability, with localized hotspots, particularly in traffic microenvironments, posing health risks to commuters. Although widely used for air quality assessment, fixed-site monitoring stations are limited by sparse distribution, high costs, and maintenance needs, making them less effective in capturing on-road pollution levels. This study utilizes a fleet of 314 taxis equipped with sensors to measure NO\textsubscript{2}, PM\text…

Googles kleines Sprachlabor: Fremdsprachen lernen mit Little Language Lessons
KI trifft Sprachtraining: Wir haben die „Little Language Lessons“ von Google getestet – taugt das Tool für schnelles, effektives Lernen einer Fremdsprache?

From afar, I'm loving the currently viral tiktok/insta livecoding genre started by Char Stiles, Jade Rowland and DJ Dave - tersely explaining all the functions of a set of strudel patterns, quickly building up a banging euphoric track while trying to suppress emotions enough to speak
I would love to see a version of this but the outcome is totally chaotic noise music that makes no sense where the person just has to shout over it to try to be heard while adding layer on layer of pat…

When Experimental Economics Meets Large Language Models: Tactics with Evidence
Shu Wang, Zijun Yao, Shuhuai Zhang, Jianuo Gai, Tracy Xiao Liu, Songfa Zhong
https://arxiv.org/abs/2505.21371

When Experimental Economics Meets Large Language Models: Tactics with Evidence
Advancements in large language models (LLMs) have sparked a growing interest in measuring and understanding their behavior through experimental economics. However, there is still a lack of established guidelines for designing economic experiments for LLMs. By combining principles from experimental economics with insights from LLM research in artificial intelligence, we outline and discuss eight practical tactics for conducting experiments with LLMs. We further perform two sets of experiments to…