@relcfp@mastodon.social2026-02-19 07:26:04
Hierarchy and Egality in South Asian Traditions https://relcfp.com/cfp/religion/south-asia/2026/02/18/hierarchy-egality-south-asia/
@relcfp@mastodon.social2026-02-19 07:26:04
@cdarwin@c.im2025-12-22 03:49:35
Tech journalist Gil Duran outlines a disturbing theory
that a growing number of Silicon Valley elites are pursuing a vision of power
not rooted in the common good,
but in profit, feudal hierarchy, and total control of the platforms that define daily life for hundreds of millions of people.
Duran dubs this emerging ideology the “Nerd Reich”
— a slurry of right-wing ideas championed by ruthless tech overlords like
Palantir founder Peter Thiel,
Tesla an…
@hex@kolektiva.social2026-02-20 20:30:38
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...
@aral@mastodon.ar.al2026-03-19 21:30:10
Dismantle every hierarchy.
@NFL@darktundra.xyz2026-01-20 21:29:36
Harbaugh: Too much focus on Giants' hierarchy https://www.espn.com/nfl/story/_/id/47674324/john-harbaugh-says-giants-power-structure-being-overblown
@saraislet@infosec.exchange2026-03-19 18:52:22
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…
@relcfp@mastodon.social2026-02-19 06:24:37
Hierarchy and Egality in South Asian Traditions https://relcfp.com/cfp/religion/south-asia/2026/02/18/hierarchy-egality-south-asia/
@midtsveen@social.linux.pizza2026-01-19 16:49:58
I just searched “anarcho-syndicalism” on Shitter and holy hell, I cannot fucking believe what I’m seeing. People are talking straight out of their asses. They treat it like a meme, like it’s some chaotic buzzword, when it means workers taking control of their own labor, seizing their workplaces, organizing through federations, striking, sabotaging, and tearing down every hierarchy built to crush them.
These people have zero historical sense. Anarcho-syndicalists fought, bled, and died …
@karlauerbach@sfba.social2026-03-15 21:48:48
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…
@relcfp@mastodon.social2026-02-19 05:45:11
Hierarchy and Egality in South Asian Traditions #acrel #Religidons #AARSBL
@blakes7bot@mas.torpidity.net2026-03-18 10:46:47
Series C, Episode 11 - Moloch
GROSE: A great many ways, Madam President. More ways than you've begun to realize. But that isn't why I summoned you to Sardos. [Grose nods at Lector and hands him a card. Lector moves to the machine, and inserts the card.]
SERVALAN: Would you say that again?
https://blake.torpidity.net/m/…
@fanf@mendeddrum.org2026-03-16 21:42:02
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/:…
@publicvoit@graz.social2026-02-15 14:25:24
@relcfp@mastodon.social2026-02-19 06:25:52
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…
@NFL@darktundra.xyz2026-03-18 19:10:38
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…
@relcfp@mastodon.social2026-02-20 16:15:57
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
@relcfp@mastodon.social2026-02-21 16:05:17
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
@joe@toot.works2026-03-03 17:08:39
maslow's hierarchy of butts 
@inthehands@hachyderm.io2025-12-27 18:59:15
Underlings are so annoying!
Sometimes you can make this problem go away by exploiting weak labor power (see: factories, agriculture, sanitation).
Sometimes you can create a toxic org culture when information •only• flows down the hierarchy, so no pushback can ever reach your sensitive ears. (Public school administrations are rife with this.)
Sometimes you can do it by making your catastrophic failures look like a string of successes to the people up the chain. (Large corporations are swimming in this.)
5/
@cowboys@darktundra.xyz2026-02-09 04:29:42
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
@raiders@darktundra.xyz2026-02-09 04:03:55
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
@arXiv_csLG_bot@mastoxiv.page2026-02-25 10:38:51
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
@axbom@axbom.me2026-01-24 12:21:13
"Donald Trump is not an interruption of the American story; he is one of its clearest chapters. He condenses habits that long predate him—mythmaking, extraction, spectacle, racial hierarchy, masculine anxiety—into a single, gaudy figure. To look at him carefully is to see the civilisation that made him."
https://richarddavidhames.substack.com/p/the-mirror-cracks
via
https://richarddavidhames.substack.com/p/the-mirror-cracks
via
@tiotasram@kolektiva.social2026-01-27 12:44:00
Content warning: ICE, racism, police brutality
An extremely simple syllogism, for which the evidence is ample and has been easily available for over a decade:
ICE : white people in Minneapolis ::
regular police : Black people everywhere in America
If you're saying "Abolish ICE" right now (as you should be) but you're hesitant to say "Abolish the police" then you're okay with the brutality as long as it's reinforcing the racial hierarchy, and that's not a good look.
I understand that "Abolish the police" is a scary thing to think about if *your* experience has been that they keep you safe, but recognize how much of that is myth vs reality, e.g. have you ever personally had a positive interaction with police, or do those all happen in stories? Also, even if they do keep you safe, is it worth it if the cost is brutality to the marginalized? (No, it's not.)
At minimum we can see the following behaviors on both sides of the syllogism:
- retaliation for legally "protected" defiance or even just observation
- random killings, with mostly-nonexistent repercussions for the officers involved
- regular widespread harassment & surveillance
-more that I don't have time to list right now. Feel free to reply with your own examples.
#AbolishICE #AbolishThePolice
@aral@mastodon.ar.al2026-02-23 17:41:10
🥳 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…
@cowboys@darktundra.xyz2026-01-05 04:44:41
@raiders@darktundra.xyz2026-01-05 05:28:48
@relcfp@mastodon.social2026-03-14 16:10:30
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…
@cowboys@darktundra.xyz2025-12-30 04:39:34
Which Super Bowl Contenders Do We Trust? https://www.foxsports.com/stories/nfl/2025-nfl-power-rankings-week-18-which-super-bowl-contenders-do-we-trust
@relcfp@mastodon.social2026-03-14 16:10:29
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…
@raiders@darktundra.xyz2025-12-30 05:23:14
Which Super Bowl Contenders Do We Trust? https://www.foxsports.com/stories/nfl/2025-nfl-power-rankings-week-18-which-super-bowl-contenders-do-we-trust
@arXiv_csLG_bot@mastoxiv.page2026-02-25 10:38:31
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
@cowboys@darktundra.xyz2025-12-23 04:49:37
2025 NFL Power Rankings Week 17: Does NFC's Road to Super Bowl Run Through The West? https://www.foxsports.com/stories/nfl/2025-nfl-power-rankings-week-17-does-nfcs-road-super-bowl-run-through-west
@raiders@darktundra.xyz2025-12-23 05:13:25
2025 NFL Power Rankings Week 17: Does NFC's Road to Super Bowl Run Through The West? https://www.foxsports.com/stories/nfl/2025-nfl-power-rankings-week-17-does-nfcs-road-super-bowl-run-through-west
@arXiv_csLG_bot@mastoxiv.page2026-02-25 16:07:47
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
@relcfp@mastodon.social2026-01-30 06:15:35
Hierarchy and Egality in South Asian Traditions
https://ift.tt/8RKPj2u
updated: Thursday, January 29, 2026 - 12:27pmfull name / name of organization: International Centre…
via Input 4 RELCFP