Tootfinder

A healthy (in body and mind),
active, frugal, sociable, mostly offline citizen
who is highly educated and informed, in full control of their data, avoiding Big Tech’s platforms and algorithms,
with a positive self-esteem and self-image,
is probably persona non grata for the tech billionaires.
But a small, insignificant nuisance, like a fly
– they don’t care about ONE.
But imagine having thousands,
then hundreds of thousands,
then millio…

A new way to describe the Fediverse and its opposition to Big Tech
I may have finally found a compelling, accessible way to describe the Fediverse - and make it appealing to people not familiar with it.

Anyone I know running this? Had an issue this week were someone got yet another vendor to send email, and our SPF is too big. Looking at solutions, sadly I can't say "stop getting vendors". Expurgate: https://github.com/smck83/expurgate

Even the Bay Area has deluded, self-important cultists.
Read how these 'pro-billionaire' protester's hilariously formed 'rationalist' ideas crumble under pressure.
☑️ San Francisco’s 'March for Billionaires' was a big bust - Mission Local
https://missionlocal.org/20…

San Francisco’s billionaire bacchanal a big bust
Only a couple dozen pro-billionaire agitators actually showed for an apparently earnest “March for Billionaires” at Alta Plaza Park.

Big Brand Energy
Sophie Wilson is on a mission to empower conscious, purpose-driven creators and entrepreneurs who understand the importance of self-development and aspire to scale their businesses and platforms into recognisable brands or movements...
Great Australian Pods Podcast Directory: https://www.gr…

Despite the hot air from government about protecting children, they've voted down our Bill to turn off the toxic algorithms.
These algorithms push toxic content promoting eating disorders, self harm, misogyny and hate.
Big Tech profits should not come before children's health.
— Paul Murphy, Member of the Irish Parliament for the party People before Profit.

Everything Big Tech gets shittier and shittier. Yes I'm using an Android phone, bad. This is all self-inflicted.
Wondering about the weather tomorrow, I click "26 Feb Tomorrow" (yes it lists "Wed 25 Feb (2026)" for today, and "Fri" for the day after tomorrow, but the day of tomorrow shall not be named, apparently.).
It takes me to a website with ads (terrible!). But it lists "Tue 30". There isn't a Tue 30 in January, February, n…

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[6/6]:
- Fast-ThinkAct: Efficient Vision-Language-Action Reasoning via Verbalizable Latent Planning
Chi-Pin Huang, Yunze Man, Zhiding Yu, Min-Hung Chen, Jan Kautz, Yu-Chiang Frank Wang, Fu-En Yang
https://arxiv.org/abs/2601.09708 https://mastoxiv.page/@arXiv_csCV_bot/115898618760721320
- Universality of Many-body Projected Ensemble for Learning Quantum Data Distribution
Quoc Hoan Tran, Koki Chinzei, Yasuhiro Endo, Hirotaka Oshima
https://arxiv.org/abs/2601.18637 https://mastoxiv.page/@arXiv_quantph_bot/115967001797773134
- FROST: Filtering Reasoning Outliers with Attention for Efficient Reasoning
Haozheng Luo, Zhuolin Jiang, Md Zahid Hasan, Yan Chen, Soumalya Sarkar
https://arxiv.org/abs/2601.19001 https://mastoxiv.page/@arXiv_csCL_bot/115972068838908815
- Analysis of Shuffling Beyond Pure Local Differential Privacy
Shun Takagi, Seng Pei Liew
https://arxiv.org/abs/2601.19154 https://mastoxiv.page/@arXiv_csDS_bot/115971701218309765
- CryoLVM: Self-supervised Learning from Cryo-EM Density Maps with Large Vision Models
Weining Fu, Kai Shu, Kui Xu, Qiangfeng Cliff Zhang
https://arxiv.org/abs/2602.02620
- XtraLight-MedMamba for Classification of Neoplastic Tubular Adenomas
Sultana, Afsar, Rahu, Singh, Shula, Combs, Forchetti, Asari
https://arxiv.org/abs/2602.04819
- Flow-Based Conformal Predictive Distributions
Trevor Harris
https://arxiv.org/abs/2602.07633 https://mastoxiv.page/@arXiv_statML_bot/116045671088130364
- GOT-Edit: Geometry-Aware Generic Object Tracking via Online Model Editing
Shih-Fang Chen, Jun-Cheng Chen, I-Hong Jhuo, Yen-Yu Lin
https://arxiv.org/abs/2602.08550 https://mastoxiv.page/@arXiv_csCV_bot/116046486984991360
- UI-Venus-1.5 Technical Report
Venus Team, et al.
https://arxiv.org/abs/2602.09082 https://mastoxiv.page/@arXiv_csCV_bot/116050980295461008
- The Wisdom of Many Queries: Complexity-Diversity Principle for Dense Retriever Training
Xincan Feng, Noriki Nishida, Yusuke Sakai, Yuji Matsumoto
https://arxiv.org/abs/2602.09448 https://mastoxiv.page/@arXiv_csIR_bot/116051022881293649
- Intent Laundering: AI Safety Datasets Are Not What They Seem
Shahriar Golchin, Marc Wetter
https://arxiv.org/abs/2602.16729 https://mastoxiv.page/@arXiv_csCR_bot/116101884238965526
- The Metaphysics We Train: A Heideggerian Reading of Machine Learning
Heman Shakeri
https://arxiv.org/abs/2602.19028 https://mastoxiv.page/@arXiv_csCY_bot/116125225694943789
- Skill-Inject: Measuring Agent Vulnerability to Skill File Attacks
David Schmotz, Luca Beurer-Kellner, Sahar Abdelnabi, Maksym Andriushchenko
https://arxiv.org/abs/2602.20156 https://mastoxiv.page/@arXiv_csCR_bot/116125330557447048
- A Very Big Video Reasoning Suite
Maijunxian Wang, et al.
https://arxiv.org/abs/2602.20159 https://mastoxiv.page/@arXiv_csCV_bot/116125664801070747
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