Tootfinder

As salty as I am about it, there's also another way to think about this. For anyone who still has connections to folks on the right (which is perhaps unlikely for anyone on this server, I digress), the cult that has consumed them thrives on isolation and grievance.
The words "you were right" have the potential to cut through the programming and open up an opportunity for reconnection. The modern conspiratorial cult of the Right has been built partially around people who were told they were wrong or were crazy. In the vast majority of cases, they were wrong and even when they were right they completely misunderstood why, but we'll skip that for now. Liberals making fun of them (even the times when they definitely earned it) has pushed them further and further into their ideological hole.
The thing about those words, "you were right," in this context is that the way they offer reconnection also requires them to take one little step of betraying their ideology to accept them. So they must choose between maintaining allegiance to a pedophile or finally getting to feel superior after years of living in an illusion of persecution.
Under the ideology of the Right, admitting one is wrong is a weakness. It is admitting defeat. They have to "own the libs" by saying things, things that they know aren't true, in order to feel dominant. But these things are often so absurd that they end up being made fun of, feeling even more weak and pathetic, reinforcing their fear and alienation.
Offering what they're looking for can offer a way out, but only if they're willing to start to recognize the thing they've supported for what it is.
And they were right about some things. They were right that Bill Gates was a terrible person. I've had plenty of liberals defend him based on his philanthropy washing, but he's awful and always has been. The Epstein links make that blatant. They intuitively recognized him and didn't trust him, even if they were wildly off base about *how and why* he shouldn't be trusted... Even if their correct mistrust was leveraged into one of the most destructive conspiracy theories ever (vaccine denial and COVID vaccine avoidance).
They were right about Bill Clinton. He was always shady as fuck. Sure, the people who attacked him at the time turned out to be even more shady but that's not the point right now. He was connected to Epstein and that was always creepy as fuck.
And the Epstein thing was an open secret that liberals ignored for a long time. It was seen as some weird thing that right wing nutjobs believed about the Clintons. But it was true. Not all of it, and there has always been an antisemitic element to the right wing interpretation or Epstein stuff, but his whole pedophile conspiracy was always kind of real.
The whole "Illuminati"/deep state thing is a vast oversimplification, an attempt to make comprehensible an incredibly complex set of interlocking and emergent behaviors. But Epstein did very much want to remake the world, to create a new world order, and he absolutely played a part in it.
The Right wing nutjobs talked about global authoritarianism, Blackhawks flying over American cities, masked men with guns disarming and executing legal gun owners in the streets. That's all happening right now.
The "FEMA concentration camps" are not actually that far off. ICE and FEMA are sister agencies, both under DHS. I'd be more than happy to call that one "close enough" in order to hear some MAGA admit that ICE is, in fact, building concentration camps.
There was always a huge millennialist element to these things. They tended to be connected to "the antichrist." It was absurd, especially for me as someone who no longer identifies as a Christian. But I'll even acquiess that to a degree. The "the number of the Beast" is 666. That's just the sum of the Hebrew spelling of "Nero." Revelations focuses a lot on Nero coming back to life after his death. His death that involved a head wound, thus the line from Revelation 13:3:
> And I saw one of his heads as if it had been mortally wounded, and his deadly wound was healed. And all the world marveled and followed the beast.
The parallels between Trump and Nero are easy to draw, and Trump's ear wound feels pretty on-the-nose for this. I don't believe in "prophecy" in this way. I think that there are patterns, and useful patterns can become encoded in beleif systems. But I will, again, happily call this one "close enough" for anyone on that side willing to also acknowledge it. I'm happy to meet on that common ground, because anyone who accepts it must recognize that their duty is to fight against it.
A lot of these correct nuggets are embedded in a framework of religious extremism and antisemitism. The vast majority of the beliefs holding these together are wildly wrong and incredibly toxic. But by giving some room to feel validated, listened to, understood, can give some room to admit things that were wrong.
Cult de-programming starts with an opening. People have to talk through their own thoughts, hear their own inconsistencies. Guiding questions can help them untangle these things for themselves. And it all starts by having enough room to feel safe, to not feel cornered, to not feel stupid. Admitting mistakes means being vulnerable, and the MAGA cult is built on fear. It's built on exploiting vulnerability and locking it away.
De-programming takes a long time. It's not easy. It takes patience. But every person who comes out does so with a powerful perspective, a deep understanding, that can be turned back against it. The best people at getting people out of cults are former members. Some of the most dedicated antifa are former fascists who understood their mistakes and dedicate their lives to fixing them.

UNEARTHLY RITES are from Finland and I think I was vaguely aware of them before- going through their debut 2024 LP now (
https://unearthlyrites.bandcamp.com/album/ecdysis) in anticipation of their new LP coming out in April, and whew, this is so promising, for the new one. This 2…

Crosslisted article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[2/3]:
- Diffusion Modulation via Environment Mechanism Modeling for Planning
Hanping Zhang, Yuhong Guo
https://arxiv.org/abs/2602.20422 https://mastoxiv.page/@arXiv_csAI_bot/116130110576555049
- Heterogeneity-Aware Client Selection Methodology For Efficient Federated Learning
Nihal Balivada, Shrey Gupta, Shashank Shreedhar Bhatt, Suyash Gupta
https://arxiv.org/abs/2602.20450 https://mastoxiv.page/@arXiv_csDC_bot/116130191233002036
- Prior-Agnostic Incentive-Compatible Exploration
Ramya Ramalingam, Osbert Bastani, Aaron Roth
https://arxiv.org/abs/2602.20465 https://mastoxiv.page/@arXiv_csGT_bot/116130245628406144
- PhyGHT: Physics-Guided HyperGraph Transformer for Signal Purification at the HL-LHC
Mohammed Rakib, Luke Vaughan, Shivang Patel, Flera Rizatdinova, Alexander Khanov, Atriya Sen
https://arxiv.org/abs/2602.20475 https://mastoxiv.page/@arXiv_hepex_bot/116130242350426528
- ActionEngine: From Reactive to Programmatic GUI Agents via State Machine Memory
Zhong, Faisal, Fran\c{c}a, Leesatapornwongsa, Szekeres, Rong, Nath
https://arxiv.org/abs/2602.20502 https://mastoxiv.page/@arXiv_csAI_bot/116130180718734838
- Inner Speech as Behavior Guides: Steerable Imitation of Diverse Behaviors for Human-AI coordination
Rakshit Trivedi, Kartik Sharma, David C Parkes
https://arxiv.org/abs/2602.20517 https://mastoxiv.page/@arXiv_csAI_bot/116130223344095649
- Stop-Think-AutoRegress: Language Modeling with Latent Diffusion Planning
Lovelace, Belardi, Zalouk, Polavaram, Kundurthy, Weinberger
https://arxiv.org/abs/2602.20528 https://mastoxiv.page/@arXiv_csCL_bot/116130628998822849
- Standard Transformers Achieve the Minimax Rate in Nonparametric Regression with $C^{s,\lambda}$ T...
Yanming Lai, Defeng Sun
https://arxiv.org/abs/2602.20555 https://mastoxiv.page/@arXiv_statML_bot/116130512372759166
- Personal Information Parroting in Language Models
Nishant Subramani, Kshitish Ghate, Mona Diab
https://arxiv.org/abs/2602.20580 https://mastoxiv.page/@arXiv_csCL_bot/116130630309564204
- Characterizing Online and Private Learnability under Distributional Constraints via Generalized S...
Mo\"ise Blanchard, Abhishek Shetty, Alexander Rakhlin
https://arxiv.org/abs/2602.20585 https://mastoxiv.page/@arXiv_statML_bot/116130525452248337
- Amortized Bayesian inference for actigraph time sheet data from mobile devices
Daniel Zhou, Sudipto Banerjee
https://arxiv.org/abs/2602.20611 https://mastoxiv.page/@arXiv_statML_bot/116130543144314661
- Knowing the Unknown: Interpretable Open-World Object Detection via Concept Decomposition Model
Xueqiang Lv, Shizhou Zhang, Yinghui Xing, Di Xu, Peng Wang, Yanning Zhang
https://arxiv.org/abs/2602.20616 https://mastoxiv.page/@arXiv_csCV_bot/116130795466851481
- On the Convergence of Stochastic Gradient Descent with Perturbed Forward-Backward Passes
Boao Kong, Hengrui Zhang, Kun Yuan
https://arxiv.org/abs/2602.20646 https://mastoxiv.page/@arXiv_mathOC_bot/116130476952419594
- DANCE: Doubly Adaptive Neighborhood Conformal Estimation
Feng, Reich, Beaglehole, Luo, Park, Yoo, Huang, Mao, Boz, Kim
https://arxiv.org/abs/2602.20652 https://mastoxiv.page/@arXiv_statML_bot/116130551664144143
- Vision-Language Models for Ergonomic Assessment of Manual Lifting Tasks: Estimating Horizontal an...
Mohammad Sadra Rajabi, Aanuoluwapo Ojelade, Sunwook Kim, Maury A. Nussbaum
https://arxiv.org/abs/2602.20658 https://mastoxiv.page/@arXiv_csCV_bot/116130809228818544
- F10.7 Index Prediction: A Multiscale Decomposition Strategy with Wavelet Transform for Performanc...
Xuran Ma, et al.
https://arxiv.org/abs/2602.20712 https://mastoxiv.page/@arXiv_astrophIM_bot/116130530693731576
- Communication-Inspired Tokenization for Structured Image Representations
Davtyan, Sahin, Haghighi, Stapf, Acuaviva, Alahi, Favaro
https://arxiv.org/abs/2602.20731 https://mastoxiv.page/@arXiv_csCV_bot/116130824303022936
- SibylSense: Adaptive Rubric Learning via Memory Tuning and Adversarial Probing
Yifei Xu, et al.
https://arxiv.org/abs/2602.20751 https://mastoxiv.page/@arXiv_csCL_bot/116130739757479992
- Assessing the Impact of Speaker Identity in Speech Spoofing Detection
Anh-Tuan Dao, Driss Matrouf, Nicholas Evans
https://arxiv.org/abs/2602.20805 https://mastoxiv.page/@arXiv_csSD_bot/116130218074059060
- Don't Ignore the Tail: Decoupling top-K Probabilities for Efficient Language Model Distillation
Sayantan Dasgupta, Trevor Cohn, Timothy Baldwin
https://arxiv.org/abs/2602.20816 https://mastoxiv.page/@arXiv_csCL_bot/116130753521420972
- DRESS: A Continuous Framework for Structural Graph Refinement
Eduar Castrillo Velilla
https://arxiv.org/abs/2602.20833 https://mastoxiv.page/@arXiv_csDS_bot/116130545112457981
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