Tootfinder

If you are an anarchist and you speak only one language, learn another one. Learn the language of your land, the indigenous language where you live. Learn the language of your ancestors, especially those languages that the state has tried to murder away. Learn an international language other than English, which have also been targets of state repression.
Prioritize languages that you both have some connection with (because it's hard to learn a language you don't care about) and languages that the state has tried to erase (because there are *reasons* those languages were targeted). Language (which can't be fully separated from culture) adds complexity. The state often tries to murder away language because (among other reasons) hierarchy is threatened by complexity. Every language adds some surveillance overhead, some more than others.

2026 NFL Power Rankings: Way-Too-Early Look At How Every Team Stacks Up https://www.foxsports.com/stories/nfl/2026-nfl-power-rankings-way-too-early-look-how-every-team-stacks-up

2026 NFL Power Rankings: Way-Too-Early Look At How Every Team Stacks Up https://www.foxsports.com/stories/nfl/2026-nfl-power-rankings-way-too-early-look-how-every-team-stacks-up

America’s war on Iran began with what was meant to be an intimidating performance of overwhelming air power.
Quickly it became another kind of conflict, with low-cost missiles and drones effectively neutralizing a superpower by punishing its allies and paralyzing energy flows.
By the time Trump tried to threaten Iran into reopening the Strait of Hormuz with a 48-hour ultimatum,
it was clear not just that the strait had become America’s singular strategic fixation but that…

The Iran War Is Revealing the Messy Middle of Our Renewable Energy Transition
When the world map of literal power changes, the political hierarchy shifts, too.

For the Skunk this year I used DxO's default color handling which has a clear hierarchy of strongly blowing out high-viz volunteers and barricades, somewhat blowing out the most strident clothing, but leaving skin and natural tones natural
#photo #photography

maslow's hierarchy of butts

Hierarchy and Egality in South Asian Traditions https://relcfp.com/cfp/religion/south-asia/2026/02/18/hierarchy-egality-south-asia/

Hierarchy and Egality in South Asian Traditions
What roles do ‘hierarchy’ and ‘egality’, as values and practices, play in the everyday lives of South Asian traditions? Hierarchy as a value in the social life of Hinduism has been much discussed. Scholarship has tended to contrast a transhistorical Hindu hierarchy with egalitarian elements of Muslim, Christian, Buddhist and Sikh thought in South Asia, framing ubiquitous caste-like social forms among the latter traditions as anomalous. Yet careful studies of everyday life in the religio…

🥳 New Kitten¹ release
• Added `initialise()` hook to `kitten.Component` instances.
This gets called at the end of the constructor and is handy if you don’t want to override the constructor and have to handle the `data` parameter and remember to call `super(data)`. You can still access passed data from `this.data`.

Note that the component is not part of the view hierarchy on the client at this point. If you have tasks you need to perform only once per page – for example, ins…

app/CHANGELOG.md at main
app - A web development kit that’s small, purrs, and loves you.

A hierarchy of spatial predictions across human visual cortex during natural vision #neuroscience

Hierarchy and Egality in South Asian Traditions https://relcfp.com/cfp/religion/south-asia/2026/02/18/hierarchy-egality-south-asia/

Hierarchy and Egality in South Asian Traditions
What roles do ‘hierarchy’ and ‘egality’, as values and practices, play in the everyday lives of South Asian traditions? Hierarchy as a value in the social life of Hinduism has been much discussed. Scholarship has tended to contrast a transhistorical Hindu hierarchy with egalitarian elements of Muslim, Christian, Buddhist and Sikh thought in South Asia, framing ubiquitous caste-like social forms among the latter traditions as anomalous. Yet careful studies of everyday life in the religio…

Well, now that it has happened we can all know, based on actual concrete proof, that not a single person in the US military hierarchy obeys the law that requires the refusal of unlawful/unconstitutional orders.
We have transitioned from a military under Constitutional and statutory limitations to a military that is a Republican Guard, or in older terms, a Praetorian Guard.
If we ever do, if ever, return to a nation of laws then every person in the entire military hierarchy is goi…

Hierarchic-EEG2Text: Assessing EEG-To-Text Decoding across Hierarchical Abstraction Levels
Anupam Sharma, Harish Katti, Prajwal Singh, Shanmuganathan Raman, Krishna Miyapuram
https://arxiv.org/abs/2602.20932 https://arxiv.org/pdf/2602.20932 https://arxiv.org/html/2602.20932
arXiv:2602.20932v1 Announce Type: new
Abstract: An electroencephalogram (EEG) records the spatially averaged electrical activity of neurons in the brain, measured from the human scalp. Prior studies have explored EEG-based classification of objects or concepts, often for passive viewing of briefly presented image or video stimuli, with limited classes. Because EEG exhibits a low signal-to-noise ratio, recognizing fine-grained representations across a large number of classes remains challenging; however, abstract-level object representations may exist. In this work, we investigate whether EEG captures object representations across multiple hierarchical levels, and propose episodic analysis, in which a Machine Learning (ML) model is evaluated across various, yet related, classification tasks (episodes). Unlike prior episodic EEG studies that rely on fixed or randomly sampled classes of equal cardinality, we adopt hierarchy-aware episode sampling using WordNet to generate episodes with variable classes of diverse hierarchy. We also present the largest episodic framework in the EEG domain for detecting observed text from EEG signals in the PEERS dataset, comprising $931538$ EEG samples under $1610$ object labels, acquired from $264$ human participants (subjects) performing controlled cognitive tasks, enabling the study of neural dynamics underlying perception, decision-making, and performance monitoring.
We examine how the semantic abstraction level affects classification performance across multiple learning techniques and architectures, providing a comprehensive analysis. The models tend to improve performance when the classification categories are drawn from higher levels of the hierarchy, suggesting sensitivity to abstraction. Our work highlights abstraction depth as an underexplored dimension of EEG decoding and motivates future research in this direction.
toXiv_bot_toot

I just published my newest project that visualizes #orgdown (#Emacs #orgmode syntax) files in a web browser:

I think I need to put into my talk this line that keeps running through my head
So many leaders want people to trust them, which is exactly backwards
In organizations, positions are typically appointed through the hierarchy and authority of the organization. However, like trust, "leadership" is earned: slowly built and quickly lost.
Asking how to earn trust means admitting you have failed, and more importantly means committing to a change. If you don't uphold…

Hierarchy and Egality in South Asian Traditions #acrel #Religidons #AARSBL

Hierarchy and Egality in South Asian Traditions
What roles do ‘hierarchy’ and ‘egality’, as values and practices, play in the everyday lives of South Asian traditions? Hierarchy as a value in the social life of Hinduism has been much discussed. Scholarship has tended to contrast a transhistorical Hindu hierarchy with egalitarian elements of Muslim, Christian, Buddhist and Sikh thought in South Asia, framing ubiquitous caste-like social forms among the latter traditions as anomalous. Yet careful studies of everyday life in the religio…

from my link log —
The asymptotic cost of address translation on memory access time.
https://arxiv.org/abs/1212.0703
saved 2020-10-21 https://dotat.at/:…

The Cost of Address Translation
Modern computers are not random access machines (RAMs). They have a memory hierarchy, multiple cores, and virtual memory. In this paper, we address the computational cost of address translation in virtual memory. Starting point for our work is the observation that the analysis of some simple algorithms (random scan of an array, binary search, heapsort) in either the RAM model or the EM model (external memory model) does not correctly predict growth rates of actual running times. We propose the …

What's interesting is that this exact set of technologies leads to decision paralysis in centralized organizations:
https://mwi.westpoint.edu/cognitive-fratricide-how-the-transparent-battlefield-creates-decision-paralysis/
The problem here is a structural one, a function of hierarchy, where the direction of the flow of power determines what technology can do and how it can e used.
In a distributed network, this information is used by a central system to distribute data back to people so they can make the most informed decision. In a centralized network, this information is used to increase the power of central control node. It's a question of who is helping whom, who is autonomous and who is support.

Dismantle every hierarchy.

The Cardinalities of Intervals of Equational Theories and Logics
Juan P. Aguilera, Nick Bezhanishvili, Tenyo Takahashi
https://arxiv.org/abs/2603.27203 https://arxiv.org/pdf/2603.27203 https://arxiv.org/html/2603.27203
arXiv:2603.27203v1 Announce Type: new
Abstract: We study the cardinality of classes of equational theories (varieties) and logics by applying descriptive set theory. We affirmatively solve open problems raised by Jackson and Lee [Trans. Am. Math. Soc. 370 (2018), pp. 4785-4812] regarding the cardinalities of subvariety lattices, and by Bezhanishvili et al. [J. Math. Log. (2025), in press] regarding the degrees of the finite model property (fmp). By coding equations and formulas by natural numbers, and theories and logics by real numbers, we examine their position in the Borel hierarchy. We prove that every interval of equational theories in a countable language corresponds to a $\boldsymbol{\Pi}^0_1$ set, and every fmp span of a normal modal logic to a $\boldsymbol{\Pi}^0_2$ set. It follows that they have cardinality either $\leq \aleph_0$ or $2^{\aleph_0}$, provably in ZFC. In the same manner, we observe that the set of pretabular extensions of a tense logic is a $\boldsymbol{\Pi}^0_2$ set, so its cardinality is either $\leq \aleph_0$ or $2^{\aleph_0}$. We also point out a negative solution to another open problem raised by Jackson and Lee [Trans. Am. Math. Soc. 370 (2018), pp. 4785-4812] regarding the existence of independent systems, which relies on Je\v{z}ek et al. [Bull. Aust. Math. Soc. 42 (1990), pp. 57-70].
toXiv_bot_toot

Bucky Brooks' top five 2026 NFL Draft prospects by position 2.0: Garrett Nussmeier rises up QB rankings https://www.nfl.com/news/bucky-brooks-top-five-2026-nfl-draft-prospects-by-position-2-0-garrett-nussmeier-rises…

2026 NFL Power Rankings: Which Teams Improved Most With the Draft? https://www.foxsports.com/stories/nfl/2026-nfl-power-rankings-which-teams-improved-most-draft

2026 NFL Power Rankings: Which Teams Improved Most With the Draft? https://www.foxsports.com/stories/nfl/2026-nfl-power-rankings-which-teams-improved-most-draft

Replaced article(s) found for physics.chem-ph. https://arxiv.org/list/physics.chem-ph/new
[1/1]:
- Proposal on the Calculation of the Ionisation-Cluster Size Distribution (I). The Model and Its Si...
Bernd Heide
https://arxiv.org/abs/2404.03961 https://mastoxiv.page/@arXiv_physicscompph_bot/112234374992126208
- Bridging chemistry and Gaussian boson sampling: A photonic hierarchy of approximations for molecu...
Jan-Lucas Eickmann, et al.
https://arxiv.org/abs/2507.19442 https://mastoxiv.page/@arXiv_quantph_bot/114930272911651358
- Benchmarking Universal Machine Learning Interatomic Potentials for Supported Nanoparticles: Decou...
Jiayan Xu, Abhirup Patra, Amar Deep Pathak, Sharan Shetty, Detlef Hohl, Roberto Car
https://arxiv.org/abs/2512.05221 https://mastoxiv.page/@arXiv_condmatmtrlsci_bot/115683143867496047
- Knowledge Distillation of a Protein Language Model Yields a Foundational Implicit Solvent Model
Justin Airas, Bin Zhang
https://arxiv.org/abs/2601.05388 https://mastoxiv.page/@arXiv_physicsbioph_bot/115881090848393264
- Universal Foundations of Thermodynamics: Entropy and Energy Beyond Equilibrium and Without Extens...
Gian Paolo Beretta
https://arxiv.org/abs/2602.09986 https://mastoxiv.page/@arXiv_quantph_bot/116051530776008418
toXiv_bot_toot

Hierarchy and Egality in South Asian Traditions
https://ift.tt/BuaCrFD
What roles do ‘hierarchy’ and ‘egality’, as values and practices, play in the everyday lives of…
via Input 4 RELCFP htt…

Hierarchy and Egality in South Asian Traditions
What roles do ‘hierarchy’ and ‘egality’, as values and practices, play in the everyday lives of South Asian traditions? Hierarchy as a value in the social life of Hinduism has been much discussed. Scholarship has tended to contrast a transhistorical Hindu hierarchy with egalitarian elements of Muslim, Christian, Buddhist and Sikh thought in South Asia, framing ubiquitous caste-like social forms among the latter traditions as anomalous. Yet careful studies of everyday life in the religio…

Meanwhile, tante points out these flaws but raises some questionable arguments of their own.
"The second aspect is often illustrated by how ships are organized: Because ships are sometimes in dangerous situations and sometimes critical decisions need to be made, the existence of ships implies the existence of a hierarchy of power relationships with a captain having the final say. Because democracy would be too slow at times."
OK, so are ships inherently authoritarian? There's a whole history of pirates who would argue otherwise...

The Self-Replication Phase Diagram: Mapping Where Life Becomes Possible in Cellular Automata Rule Space
Don Yin
https://arxiv.org/abs/2603.25239 https://arxiv.org/pdf/2603.25239 https://arxiv.org/html/2603.25239
arXiv:2603.25239v1 Announce Type: new
Abstract: What substrate features allow life? We exhaustively classify all 262,144 outer-totalistic binary cellular automata rules with Moore neighbourhood for self-replication and produce phase diagrams in the $(\lambda, F)$ plane, where $\lambda$ is Langton's rule density and $F$ is a background-stability parameter. Of these rules, 20,152 (7.69%) support pattern proliferation, concentrated at low rule density ($\lambda \approx 0.15$--$0.25$) and low-to-moderate background stability ($F \approx 0.2$--$0.3$), in the weakly supercritical regime (Derrida coefficient $\mu = 1.81$ for replicators vs. $1.39$ for non-replicators). Self-replicating rules are more approximately mass-conserving (mass-balance 0.21 vs. 0.34), and this generalises to $k{=}3$ Moore rules. A three-tier detection hierarchy (pattern proliferation, extended-length confirmation, and causal perturbation) yields an estimated 1.56% causal self-replication rate. Self-replication rate increases monotonically with neighbourhood size under equalised detection: von Neumann 4.79%, Moore 7.69%, extended Moore 16.69%. These results identify background stability and approximate mass conservation as the primary axes of the self-replication phase boundary.
toXiv_bot_toot

From Isolation to Integration: Building an Adaptive Expert Forest for Pre-Trained Model-based Class-Incremental Learning
Ruiqi Liu, Boyu Diao, Hangda Liu, Zhulin An, Fei Wang, Yongjun Xu
https://arxiv.org/abs/2602.20911 https://arxiv.org/pdf/2602.20911 https://arxiv.org/html/2602.20911
arXiv:2602.20911v1 Announce Type: new
Abstract: Class-Incremental Learning (CIL) requires models to learn new classes without forgetting old ones. A common method is to freeze a pre-trained model and train a new, lightweight adapter for each task. While this prevents forgetting, it treats the learned knowledge as a simple, unstructured collection and fails to use the relationships between tasks. To this end, we propose the Semantic-guided Adaptive Expert Forest (SAEF), a new method that organizes adapters into a structured hierarchy for better knowledge sharing. SAEF first groups tasks into conceptual clusters based on their semantic relationships. Then, within each cluster, it builds a balanced expert tree by creating new adapters from merging the adapters of similar tasks. At inference time, SAEF finds and activates a set of relevant experts from the forest for any given input. The final prediction is made by combining the outputs of these activated experts, weighted by how confident each expert is. Experiments on several benchmark datasets show that SAEF achieves SOTA performance.
toXiv_bot_toot

Propaganda of the deed generally does the opposite of what it's supposed to do: it alienates rather than activates, destroying the movement it comes from. Until it doesn't. Until it actually sparks a revolution.
But there is a prerequisite for a successful revolution. That is an alternative system to pivot into as the old one collapses. That alternative is *far more dangerous* than any one-off action, up to and including literally killing a king or an emperor.
People will eventually rise up. That's just a matter of time. The question is what's left after everything gets burned down. That's a far more important question than, "is it happening?" It's happening (sometimes slowly, sometimes quickly), what's next?
Hierarchy manifests complexity beyond its ability to manage. We're seeing that now, we will see it more. Distributed authority is more stable. Build a distributed society within the burned out warehouse of the hierarchical one.

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[2/6]:
- Performance Asymmetry in Model-Based Reinforcement Learning
Jing Yu Lim, Rushi Shah, Zarif Ikram, Samson Yu, Haozhe Ma, Tze-Yun Leong, Dianbo Liu
https://arxiv.org/abs/2505.19698 https://mastoxiv.page/@arXiv_csLG_bot/114578810521008766
- Towards Robust Real-World Multivariate Time Series Forecasting: A Unified Framework for Dependenc...
Jinkwan Jang, Hyungjin Park, Jinmyeong Choi, Taesup Kim
https://arxiv.org/abs/2506.08660 https://mastoxiv.page/@arXiv_csLG_bot/114664238967892509
- Wasserstein Barycenter Soft Actor-Critic
Zahra Shahrooei, Ali Baheri
https://arxiv.org/abs/2506.10167 https://mastoxiv.page/@arXiv_csLG_bot/114675175949432731
- Foundation Models for Causal Inference via Prior-Data Fitted Networks
Yuchen Ma, Dennis Frauen, Emil Javurek, Stefan Feuerriegel
https://arxiv.org/abs/2506.10914 https://mastoxiv.page/@arXiv_csLG_bot/114675529854402158
- FREQuency ATTribution: benchmarking frequency-based occlusion for time series data
Dominique Mercier, Andreas Dengel, Sheraz Ahmed
https://arxiv.org/abs/2506.18481 https://mastoxiv.page/@arXiv_csLG_bot/114738421450807709
- Complexity-aware fine-tuning
Andrey Goncharov, Daniil Vyazhev, Petr Sychev, Edvard Khalafyan, Alexey Zaytsev
https://arxiv.org/abs/2506.21220 https://mastoxiv.page/@arXiv_csLG_bot/114754764750730849
- Transfer Learning in Infinite Width Feature Learning Networks
Clarissa Lauditi, Blake Bordelon, Cengiz Pehlevan
https://arxiv.org/abs/2507.04448 https://mastoxiv.page/@arXiv_csLG_bot/114818005803079705
- A hierarchy tree data structure for behavior-based user segment representation
Liu, Kang, Iyer, Malik, Li, Wang, Lu, Zhao, Wang, Liu, Liu, Liang, Yu
https://arxiv.org/abs/2508.01115 https://mastoxiv.page/@arXiv_csLG_bot/114975999992144374
- One-Step Flow Q-Learning: Addressing the Diffusion Policy Bottleneck in Offline Reinforcement Lea...
Thanh Nguyen, Chang D. Yoo
https://arxiv.org/abs/2508.13904 https://mastoxiv.page/@arXiv_csLG_bot/115060568241390847
- Uncertainty Propagation Networks for Neural Ordinary Differential Equations
Hadi Jahanshahi, Zheng H. Zhu
https://arxiv.org/abs/2508.16815 https://mastoxiv.page/@arXiv_csLG_bot/115094785677272005
- Learning Unified Representations from Heterogeneous Data for Robust Heart Rate Modeling
Zhengdong Huang, Zicheng Xie, Wentao Tian, Jingyu Liu, Lunhong Dong, Peng Yang
https://arxiv.org/abs/2508.21785 https://mastoxiv.page/@arXiv_csLG_bot/115128450608548173
- Monte Carlo Tree Diffusion with Multiple Experts for Protein Design
Liu, Cao, Jiang, Luo, Duan, Wang, Sosnick, Xu, Stevens
https://arxiv.org/abs/2509.15796 https://mastoxiv.page/@arXiv_csLG_bot/115247429156900905
- From Samples to Scenarios: A New Paradigm for Probabilistic Forecasting
Xilin Dai, Zhijian Xu, Wanxu Cai, Qiang Xu
https://arxiv.org/abs/2509.19975 https://mastoxiv.page/@arXiv_csLG_bot/115264498084813952
- Why High-rank Neural Networks Generalize?: An Algebraic Framework with RKHSs
Yuka Hashimoto, Sho Sonoda, Isao Ishikawa, Masahiro Ikeda
https://arxiv.org/abs/2509.21895 https://mastoxiv.page/@arXiv_csLG_bot/115287261047939306
- From Parameters to Behaviors: Unsupervised Compression of the Policy Space
Davide Tenedini, Riccardo Zamboni, Mirco Mutti, Marcello Restelli
https://arxiv.org/abs/2509.22566 https://mastoxiv.page/@arXiv_csLG_bot/115287379672141023
- RHYTHM: Reasoning with Hierarchical Temporal Tokenization for Human Mobility
Haoyu He, Haozheng Luo, Yan Chen, Qi R. Wang
https://arxiv.org/abs/2509.23115 https://mastoxiv.page/@arXiv_csLG_bot/115293273559547106
- Polychromic Objectives for Reinforcement Learning
Jubayer Ibn Hamid, Ifdita Hasan Orney, Ellen Xu, Chelsea Finn, Dorsa Sadigh
https://arxiv.org/abs/2509.25424 https://mastoxiv.page/@arXiv_csLG_bot/115298579764580635
- Recursive Self-Aggregation Unlocks Deep Thinking in Large Language Models
Siddarth Venkatraman, et al.
https://arxiv.org/abs/2509.26626 https://mastoxiv.page/@arXiv_csLG_bot/115298789487177431
- Cautious Weight Decay
Chen, Li, Liang, Su, Xie, Pierse, Liang, Lao, Liu
https://arxiv.org/abs/2510.12402 https://mastoxiv.page/@arXiv_csLG_bot/115377759317818093
- TeamFormer: Shallow Parallel Transformers with Progressive Approximation
Wei Wang, Xiao-Yong Wei, Qing Li
https://arxiv.org/abs/2510.15425 https://mastoxiv.page/@arXiv_csLG_bot/115405933861293858
- Latent-Augmented Discrete Diffusion Models
Dario Shariatian, Alain Durmus, Umut Simsekli, Stefano Peluchetti
https://arxiv.org/abs/2510.18114 https://mastoxiv.page/@arXiv_csLG_bot/115417332500265972
- Predicting Metabolic Dysfunction-Associated Steatotic Liver Disease using Machine Learning Method...
Mary E. An, Paul Griffin, Jonathan G. Stine, Ramakrishna Balakrishnan, Soundar Kumara
https://arxiv.org/abs/2510.22293 https://mastoxiv.page/@arXiv_csLG_bot/115451746201804373
toXiv_bot_toot

Hierarchy and Egality in South Asian Traditions
https://ift.tt/wlW3xKk
updated: Thursday, January 29, 2026 - 12:27pmfull name / name of organization: International Centre…
via Input 4 RELCFP

Hierarchy and Egality in South Asian Traditions
https://ift.tt/VqGvXz7
updated: Thursday, January 29, 2026 - 12:27pmfull name / name of organization: International Centre…
via Input 4 RELCFP

Disability and Hierarchy
https://ift.tt/MrJA16k
updated: Friday, March 13, 2026 - 1:38pmfull name / name of organization: Modern Language…
via Input 4 RELCFP https://if…

Disability and Hierarchy
https://ift.tt/MrJA16k
updated: Friday, March 13, 2026 - 1:38pmfull name / name of organization: Modern Language…
via Input 4 RELCFP https://if…