Tootfinder

I keep coming back to the mirror dualities of the oppressed and oppressor under authoritarianism.
The oppressed is portrayed as both weak and godlike. The stereotypes are always some variation on sloth and incompetence, but yet somehow also a menace capable of destroying the "pure" society. To use the most relevant current example, Antifa being both little femme soy boys who would always get beat up by "real men" while also being an international terrorist organization on the brink of overthrowing the US government, the unarmed presence of whom makes the heavily armed agents of ICE flee for their lives. Antifa is both having absolutely no impact on ICE, and also having such an impact on ICE that the military needs to come in to protect them. The contradiction is obvious but never seems to occur to those who hold both to be true at the same time.
But few talk about the duality of the oppressor. The sovereign throughout history has always been both a ruler above the law, sometimes even the representative or incarnation of a divine force. Yet, this same superhuman/god-man is also a baby who needs constant care. This is absolutely a through line from the very earliest records of sovereign cults to modern cult leaders, CEOs, and Trump today. Power, for these people, is expressed both as the ability to force others to enact their will and in the ability to compel others to care for them. Can any of these "men" cook? Can they fix anything themselves? They are driven everywhere, cooked for all the time, constantly protected from danger. Kings are still dressed, at least for rituals. I could dissect masculinity here, but that's a whole thing.
It is as though the drive to care for our children, who must be taught to behave within acceptable norms, is hijacked by "leaders" who demand our care and attention... even at the expense of our literal children. And recently we've seen some of those very CEOs, with LLMs and return to office demands, show that their judgment is also little better than children, making decisions while pretending to understand a subject.
The oppressed are portrayed as both god-like and impotent and are, in fact, neither. Meanwhile the rulers portray themselves only as invulnerable and are, in fact, childish in their ability to survive without constant support. Their greatest fear from the collapse of society is figuring out how to make sure people keep taking care of them.
It just keeps rattling around in my head.
#USPol

A Network Digital Twin of a 5G Private Network: Designing a Proof-of-Concept from Theory to Practice
Cristina Emilia Costa, Tatenda Horiro Zhou, Fabrizio Granelli
https://arxiv.org/abs/2510.12458

A Network Digital Twin of a 5G Private Network: Designing a Proof-of-Concept from Theory to Practice
Network Digital Twins represent a key technology in future networks, expected to provide the capability to perform accurate analysis and predictions about the behaviour of 6G mobile networks. However, despite the availability of several theoretical works on the subject, still very few examples of actual implementations of Network Digital Twin are available. This paper provides a detailed description about the characteristics of Network Digital Twin and provides a practical example about real de…

Some Reflections on Sliding Mode Designs in Control Systems: An Example of Adaptive Tracking Control for Simple Mechanical Systems With Friction Without Measurement of Velocity
Romeo Ortega, Leyan Fang, Jose Guadalupe Romero
https://arxiv.org/abs/2510.07675

Some Reflections on Sliding Mode Designs in Control Systems: An Example of Adaptive Tracking Control for Simple Mechanical Systems With Friction Without Measurement of Velocity
The objective of this note is to share some reflections of the authors regarding the use of sliding mode designs in control systems. We believe the abundant, and ever increasing, appearance of this kind of works on our scientific publications deserves some critical evaluation of their actual role, relevance and pertinence. First, we discuss the procedure followed by most of these designs -- illustrated with examples from the literature. Second, we bring to the readers attention several aspects …

Adversarial Attacks Leverage Interference Between Features in Superposition
Edward Stevinson, Lucas Prieto, Melih Barsbey, Tolga Birdal
https://arxiv.org/abs/2510.11709 https://…

Adversarial Attacks Leverage Interference Between Features in Superposition
Fundamental questions remain about when and why adversarial examples arise in neural networks, with competing views characterising them either as artifacts of the irregularities in the decision landscape or as products of sensitivity to non-robust input features. In this paper, we instead argue that adversarial vulnerability can stem from efficient information encoding in neural networks. Specifically, we show how superposition - where networks represent more features than they have dimensions …

Average Kernel Sizes -- Computable Sharp Accuracy Bounds for Inverse Problems
Nina M. Gottschling, David Iagaru, Jakob Gawlikowski, Ioannis Sgouralis
https://arxiv.org/abs/2510.10229

Average Kernel Sizes -- Computable Sharp Accuracy Bounds for Inverse Problems
The reconstruction of an unknown quantity from noisy measurements is a mathematical problem relevant in most applied sciences, for example, in medical imaging, radar inverse scattering, or astronomy. This underlying mathematical problem is often an ill-posed (non-linear) reconstruction problem, referred to as an ill-posed inverse problem. To tackle such problems, there exist a myriad of methods to design approximate inverse maps, ranging from optimization-based approaches, such as compressed se…

Uncertainty Quantification for Multi-level Models Using the Survey-Weighted Pseudo-Posterior
Matthew R. Williams, F. Hunter McGuire, Terrance D. Savitsky
https://arxiv.org/abs/2510.09401

Uncertainty Quantification for Multi-level Models Using the Survey-Weighted Pseudo-Posterior
Parameter estimation and inference from complex survey samples typically focuses on global model parameters whose estimators have asymptotic properties, such as from fixed effects regression models. We present a motivating example of Bayesian inference for a multi-level or mixed effects model in which both the local parameters (e.g. group level random effects) and the global parameters may need to be adjusted for the complex sampling design. We evaluate the limitations of the survey-weighted ps…

Pragyaan: Designing and Curating High-Quality Cultural Post-Training Datasets for Indian Languages
Neel Prabhanjan Rachamalla, Aravind Konakalla, Gautam Rajeev, Ashish Kulkarni, Chandra Khatri, Shubham Agarwal
https://arxiv.org/abs/2510.07000

Pragyaan: Designing and Curating High-Quality Cultural Post-Training Datasets for Indian Languages
The effectiveness of Large Language Models (LLMs) depends heavily on the availability of high-quality post-training data, particularly instruction-tuning and preference-based examples. Existing open-source datasets, however, often lack multilingual coverage, cultural grounding, and suffer from task diversity gaps that are especially pronounced for Indian languages. We introduce a human-in-the-loop pipeline that combines translations with synthetic expansion to produce reliable and diverse Indic…

Testing the equality of estimable parameters across many populations
Marcos Romero-Madro\~nal, Mar\'ia de los Remedios Sillero-Denamiel, Mar\'ia Dolores Jim\'enez-Gamero
https://arxiv.org/abs/2510.06763

Testing the equality of estimable parameters across many populations
The comparison of a parameter in $k$ populations is a classical problem in statistics. Testing for the equality of means or variances are typical examples. Most procedures designed to deal with this problem assume that $k$ is fixed and that samples with increasing sample sizes are available from each population. This paper introduces and studies a test for the comparison of an estimable parameter across $k$ populations, when $k$ is large and the sample sizes from each population are small when …

Invariant Price of Anarchy: a Metric for Welfarist Traffic Control
Ilia Shilov, Mingjia He, Heinrich H. Nax, Emilio Frazzoli, Gioele Zardini, Saverio Bolognani
https://arxiv.org/abs/2512.05843 https://arxiv.org/pdf/2512.05843 https://arxiv.org/html/2512.05843
arXiv:2512.05843v1 Announce Type: new
Abstract: The Price of Anarchy (PoA) is a standard metric for quantifying inefficiency in socio-technical systems, widely used to guide policies like traffic tolling. Conventional PoA analysis relies on exact numerical costs. However, in many settings, costs represent agents' preferences and may be defined only up to possibly arbitrary scaling and shifting, representing informational and modeling ambiguities. We observe that while such transformations preserve equilibrium and optimal outcomes, they change the PoA value. To resolve this issue, we rely on results from Social Choice Theory and define the Invariant PoA. By connecting admissible transformations to degrees of comparability of agents' costs, we derive the specific social welfare functions which ensure that efficiency evaluations do not depend on arbitrary rescalings or translations of individual costs. Case studies on a toy example and the Zurich network demonstrate that identical tolling strategies can lead to substantially different efficiency estimates depending on the assumed comparability. Our framework thus demonstrates that explicit axiomatic foundations are necessary in order to define efficiency metrics and to appropriately guide policy in large-scale infrastructure design robustly and effectively.
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