Tootfinder

Some City Some Nature V 🏙️🪾
一些城一些自然 V 🏙️🪾
📷 Nikon F4E
🎞️ ERA 100, expired 1993
#filmphotography #Photography #blackandwhite

StŸt Ukraine.
Og så bagefter tænk lige vi i Danmark kunne komme til at overleve sådan en strategi..
https://fediscience.org/@Ruth_Mottram/116142077788041706
Ruth_Mottram - Fuck Russia.
Seriously.
Genstart: Kulden sætter sig i knoglerne
Episode webpage: https://www.dr.dk/lyd/special-radio/genstart-2642056922000
Media file: https://api.dr.dk/podcasts/v1/assets/urn:dr:podcast:item:11802660046/5789fc409d99f0dde8b92feb3aabf99c3cc1d8c9e6d690427e98a0a4064dbe29.mp3

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
toXiv_bot_toot

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.

RE: #emojis #linguistik #vorlesung
PS: Vielen Dank für die Einladung, liebe Uni Bern!! 🥰 https://tobira.unibe.ch/~embed/!v/K7Yd8YToe3L

Looking at this property description in Glasgow on #Rightmove. The clouds from one photo to the next seemed strangely similar so I took a screenshot of them from each different room and outside POV...
they're all the same clouds
They have CGI-ed the clouds?? Why?? Is this even legal?
I'm definitely not going to trust this agency in future.. "Keys estate ag…

Urban Demons VII 👻
城市鬼魂 VII 👻
📷 Zeiss IKON Super Ikonta 533/16
🎞️ Ilford HP5 400 Plus, expired 1993
If you like my work, buy me a coffee from PayPal https://www.paypal.com/paypalme/ydcdingsite

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[5/6]:
- Watermarking Degrades Alignment in Language Models: Analysis and Mitigation
Apurv Verma, NhatHai Phan, Shubhendu Trivedi
https://arxiv.org/abs/2506.04462 https://mastoxiv.page/@arXiv_csCL_bot/114635190037336859
- Sensory-Motor Control with Large Language Models via Iterative Policy Refinement
J\^onata Tyska Carvalho, Stefano Nolfi
https://arxiv.org/abs/2506.04867 https://mastoxiv.page/@arXiv_csAI_bot/114635187854195641
- ICE-ID: A Novel Historical Census Dataset for Longitudinal Identity Resolution
de Carvalho, Popov, Kaatee, Correia, Th\'orisson, Li, Bj\"ornsson, Sigur{\dh}arson, Dibangoye
https://arxiv.org/abs/2506.13792 https://mastoxiv.page/@arXiv_csAI_bot/114703312162525342
- Feedback-driven recurrent quantum neural network universality
Lukas Gonon, Rodrigo Mart\'inez-Pe\~na, Juan-Pablo Ortega
https://arxiv.org/abs/2506.16332 https://mastoxiv.page/@arXiv_quantph_bot/114732532383196043
- Programming by Backprop: An Instruction is Worth 100 Examples When Finetuning LLMs
Cook, Sapora, Ahmadian, Khan, Rocktaschel, Foerster, Ruis
https://arxiv.org/abs/2506.18777 https://mastoxiv.page/@arXiv_csAI_bot/114738213040759661
- Stochastic Quantum Spiking Neural Networks with Quantum Memory and Local Learning
Jiechen Chen, Bipin Rajendran, Osvaldo Simeone
https://arxiv.org/abs/2506.21324 https://mastoxiv.page/@arXiv_csNE_bot/114754367612728319
- Enjoying Non-linearity in Multinomial Logistic Bandits: A Minimax-Optimal Algorithm
Pierre Boudart (SIERRA), Pierre Gaillard (Thoth), Alessandro Rudi (PSL, DI-ENS, Inria)
https://arxiv.org/abs/2507.05306 https://mastoxiv.page/@arXiv_statML_bot/114822374525501660
- Characterizing State Space Model and Hybrid Language Model Performance with Long Context
Saptarshi Mitra, Rachid Karami, Haocheng Xu, Sitao Huang, Hyoukjun Kwon
https://arxiv.org/abs/2507.12442 https://mastoxiv.page/@arXiv_csAR_bot/114867589638074984
- Is Exchangeability better than I.I.D to handle Data Distribution Shifts while Pooling Data for Da...
Ayush Roy, Samin Enam, Jun Xia, Won Hwa Kim, Vishnu Suresh Lokhande
https://arxiv.org/abs/2507.19575 https://mastoxiv.page/@arXiv_csCV_bot/114935399825741861
- TASER: Table Agents for Schema-guided Extraction and Recommendation
Nicole Cho, Kirsty Fielding, William Watson, Sumitra Ganesh, Manuela Veloso
https://arxiv.org/abs/2508.13404 https://mastoxiv.page/@arXiv_csAI_bot/115060386723032051
- Morphology-Aware Peptide Discovery via Masked Conditional Generative Modeling
Nuno Costa, Julija Zavadlav
https://arxiv.org/abs/2509.02060 https://mastoxiv.page/@arXiv_qbioBM_bot/115139546511384706
- PCPO: Proportionate Credit Policy Optimization for Aligning Image Generation Models
Jeongjae Lee, Jong Chul Ye
https://arxiv.org/abs/2509.25774 https://mastoxiv.page/@arXiv_csCV_bot/115298580419859537
- Multi-hop Deep Joint Source-Channel Coding with Deep Hash Distillation for Semantically Aligned I...
Didrik Bergstr\"om, Deniz G\"und\"uz, Onur G\"unl\"u
https://arxiv.org/abs/2510.06868 https://mastoxiv.page/@arXiv_csIT_bot/115343320768797486
- MoMaGen: Generating Demonstrations under Soft and Hard Constraints for Multi-Step Bimanual Mobile...
Chengshu Li, et al.
https://arxiv.org/abs/2510.18316 https://mastoxiv.page/@arXiv_csRO_bot/115416889485910123
- A Spectral Framework for Graph Neural Operators: Convergence Guarantees and Tradeoffs
Roxanne Holden, Luana Ruiz
https://arxiv.org/abs/2510.20954 https://mastoxiv.page/@arXiv_statML_bot/115445273121677005
- Breaking Agent Backbones: Evaluating the Security of Backbone LLMs in AI Agents
Bazinska, Mathys, Casucci, Rojas-Carulla, Davies, Souly, Pfister
https://arxiv.org/abs/2510.22620 https://mastoxiv.page/@arXiv_csCR_bot/115451397563132982
- Uncertainty Calibration of Multi-Label Bird Sound Classifiers
Raphael Schwinger, Ben McEwen, Vincent S. Kather, Ren\'e Heinrich, Lukas Rauch, Sven Tomforde
https://arxiv.org/abs/2511.08261 https://mastoxiv.page/@arXiv_csSD_bot/115535982708483824
- Two-dimensional RMSD projections for reaction path visualization and validation
Rohit Goswami (Institute IMX and Lab-COSMO, \'Ecole polytechnique f\'ed\'erale de Lausanne)
https://arxiv.org/abs/2512.07329 https://mastoxiv.page/@arXiv_physicschemph_bot/115688910885717951
- Distribution-informed Online Conformal Prediction
Dongjian Hu, Junxi Wu, Shu-Tao Xia, Changliang Zou
https://arxiv.org/abs/2512.07770 https://mastoxiv.page/@arXiv_statML_bot/115689281155541568
- Coupling Experts and Routers in Mixture-of-Experts via an Auxiliary Loss
Ang Lv, Jin Ma, Yiyuan Ma, Siyuan Qiao
https://arxiv.org/abs/2512.23447 https://mastoxiv.page/@arXiv_csCL_bot/115808311310246601
toXiv_bot_toot

Monumental 🪦
纪念 🪦
📷 Nikon F4E
🎞️ Ilford HP5 Plus 400, expired 1993
#filmphotography #Photography #blackandwhite

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[3/6]:
- Towards Scalable Oversight via Partitioned Human Supervision
Ren Yin, Takashi Ishida, Masashi Sugiyama
https://arxiv.org/abs/2510.22500 https://mastoxiv.page/@arXiv_csLG_bot/115451787490434401
- ContextPilot: Fast Long-Context Inference via Context Reuse
Yinsicheng Jiang, Yeqi Huang, Liang Cheng, Cheng Deng, Xuan Sun, Luo Mai
https://arxiv.org/abs/2511.03475 https://mastoxiv.page/@arXiv_csLG_bot/115502245581974540
- Metabolomic Biomarker Discovery for ADHD Diagnosis Using Interpretable Machine Learning
Nabil Belacel, Mohamed Rachid Boulassel
https://arxiv.org/abs/2601.11283 https://mastoxiv.page/@arXiv_csLG_bot/115921183182326799
- PhysE-Inv: A Physics-Encoded Inverse Modeling approach for Arctic Snow Depth Prediction
Akila Sampath, Vandana Janeja, Jianwu Wang
https://arxiv.org/abs/2601.17074
- SAGE-5GC: Security-Aware Guidelines for Evaluating Anomaly Detection in the 5G Core Network
Cristian Manca, Christian Scano, Giorgio Piras, Fabio Brau, Maura Pintor, Battista Biggio
https://arxiv.org/abs/2602.03596
- LORE: Jointly Learning the Intrinsic Dimensionality and Relative Similarity Structure From Ordina...
Anand, Helbling, Davenport, Berman, Alagapan, Rozell
https://arxiv.org/abs/2602.04192
- Towards Robust Scaling Laws for Optimizers
Alexandra Volkova, Mher Safaryan, Christoph H. Lampert, Dan Alistarh
https://arxiv.org/abs/2602.07712 https://mastoxiv.page/@arXiv_csLG_bot/116046369672796465
- Do We Need Adam? Surprisingly Strong and Sparse Reinforcement Learning with SGD in LLMs
Sagnik Mukherjee, Lifan Yuan, Pavan Jayasinha, Dilek Hakkani-T\"ur, Hao Peng
https://arxiv.org/abs/2602.07729 https://mastoxiv.page/@arXiv_csLG_bot/116046377539155485
- AceGRPO: Adaptive Curriculum Enhanced Group Relative Policy Optimization for Autonomous Machine L...
Yuzhu Cai, Zexi Liu, Xinyu Zhu, Cheng Wang, Siheng Chen
https://arxiv.org/abs/2602.07906 https://mastoxiv.page/@arXiv_csLG_bot/116046423413650658
- VESPO: Variational Sequence-Level Soft Policy Optimization for Stable Off-Policy LLM Training
Guobin Shen, Chenxiao Zhao, Xiang Cheng, Lei Huang, Xing Yu
https://arxiv.org/abs/2602.10693 https://mastoxiv.page/@arXiv_csLG_bot/116057229834947730
- KBVQ-MoE: KLT-guided SVD with Bias-Corrected Vector Quantization for MoE Large Language Models
Zukang Xu, Zhixiong Zhao, Xing Hu, Zhixuan Chen, Dawei Yang
https://arxiv.org/abs/2602.11184 https://mastoxiv.page/@arXiv_csLG_bot/116062537528208461
- MUSE: Multi-Tenant Model Serving With Seamless Model Updates
Correia, Ferreira, Martins, Bento, Guerreiro, Pereira, Gomes, Bono, Ferreira, Bizarro
https://arxiv.org/abs/2602.11776 https://mastoxiv.page/@arXiv_csLG_bot/116062952355379801
- Pawsterior: Variational Flow Matching for Structured Simulation-Based Inference
Jorge Carrasco-Pollo, Floor Eijkelboom, Jan-Willem van de Meent
https://arxiv.org/abs/2602.13813 https://mastoxiv.page/@arXiv_csLG_bot/116085828112928218
- Silent Inconsistency in Data-Parallel Full Fine-Tuning: Diagnosing Worker-Level Optimization Misa...
Hong Li, Zhen Zhou, Honggang Zhang, Yuping Luo, Xinyue Wang, Han Gong, Zhiyuan Liu
https://arxiv.org/abs/2602.14462 https://mastoxiv.page/@arXiv_csLG_bot/116085997857526328
- Divine Benevolence is an $x^2$: GLUs scale asymptotically faster than MLPs
Alejandro Francisco Queiruga
https://arxiv.org/abs/2602.14495 https://mastoxiv.page/@arXiv_csLG_bot/116086011618741857
- \"UberWeb: Insights from Multilingual Curation for a 20-Trillion-Token Dataset
DatologyAI, et al.
https://arxiv.org/abs/2602.15210 https://mastoxiv.page/@arXiv_csLG_bot/116090912256712568
- GLM-5: from Vibe Coding to Agentic Engineering
GLM-5-Team, et al.
https://arxiv.org/abs/2602.15763 https://mastoxiv.page/@arXiv_csLG_bot/116091080686771018
- Anatomy of Capability Emergence: Scale-Invariant Representation Collapse and Top-Down Reorganizat...
Jayadev Billa
https://arxiv.org/abs/2602.15997 https://mastoxiv.page/@arXiv_csLG_bot/116096541546306333
- AI-CARE: Carbon-Aware Reporting Evaluation Metric for AI Models
KC Santosh, Srikanth Baride, Rodrigue Rizk
https://arxiv.org/abs/2602.16042 https://mastoxiv.page/@arXiv_csLG_bot/116096581524696028
- Beyond Message Passing: A Symbolic Alternative for Expressive and Interpretable Graph Learning
Chuqin Geng, Li Zhang, Haolin Ye, Ziyu Zhao, Yuhe Jiang, Tara Saba, Xinyu Wang, Xujie Si
https://arxiv.org/abs/2602.16947 https://mastoxiv.page/@arXiv_csLG_bot/116102426238903124
toXiv_bot_toot