Tootfinder

Sampling in the #OpenTelemetry Collector
https://opentelemetry.io/docs/concepts/sampling/

Woo hoo! You all get to start adding stuff to Cosmik Network’s Semble: a social bookmarking tool built on ATProto, so all your data is stored in your own account https://semble.so
I’ve been using it for weeks, have it as a PWA on my phone, and it’s been great to just get the basics of saving links somewhere.

Fascists don't get to claim whatever symbols they want. We can and should defend them.
https://www.offmessage.net/p/fascists-dont-get-to-claim-symbols

Fascists Don't Get To Claim Whatever Symbols They Want
Particularly these soft, weak men.

A study finds that as few as 250 malicious documents can produce a "backdoor" vulnerability in an LLM, regardless of model size or training data volume (Anthropic)
https://www.anthropic.com/research/small-samples-poison

A small number of samples can poison LLMs of any size
Anthropic research on data-poisoning attacks in large language models

Sampling Strategies for Robust Universal Quadrupedal Locomotion Policies
David Rytz, Kim Tien Ly, Ioannis Havoutis
https://arxiv.org/abs/2510.07094 https://

Sampling Strategies for Robust Universal Quadrupedal Locomotion Policies
This work focuses on sampling strategies of configuration variations for generating robust universal locomotion policies for quadrupedal robots. We investigate the effects of sampling physical robot parameters and joint proportional-derivative gains to enable training a single reinforcement learning policy that generalizes to multiple parameter configurations. Three fundamental joint gain sampling strategies are compared: parameter sampling with (1) linear and polynomial function mappings of ma…

A Broader View of Thompson Sampling
Yanlin Qu, Hongseok Namkoong, Assaf Zeevi
https://arxiv.org/abs/2510.07208 https://arxiv.org/pdf/2510.07208

A Broader View of Thompson Sampling
Thompson Sampling is one of the most widely used and studied bandit algorithms, known for its simple structure, low regret performance, and solid theoretical guarantees. Yet, in stark contrast to most other families of bandit algorithms, the exact mechanism through which posterior sampling (as introduced by Thompson) is able to "properly" balance exploration and exploitation, remains a mystery. In this paper we show that the core insight to address this question stems from recasting Thompson Sa…

«There is a massive power in standing for something that you'll never get by standing for whatever the most recent polls show. It's an attraction. It moves the lines of ought-to-be. It defines what is shameful by showing what is inspiring. It creates someplace else for people who have chosen shameful identities to go, if they so choose.»
The Extraordinary Power of Standing For Something
https://www.the-reframe.com/the-extraordinary-power-of-standing-for-something/

Hat Bello sein Bewegungsziel erreicht?
Nach Kindern sind die Haustiere dran!
https://www.sueddeutsche.de/panorama/gps-tracker-haustiere-fitness-apps-uebersicht-sinnvoll-li.3305272

Fitness-Tracker für Tiere liegen im Trend: Wie sinnvoll sind die Geräte?
Das Geschäft mit Haustiertrackern boomt. Die Geräte liefern Gesundheitswerte wie Ruhepuls, Schlaftiefe oder Schrittzahl. Braucht’s das?

Refinement-based Christoffel sampling for least squares approximation in non-orthogonal bases
Astird Herremans, Ben Adcock
https://arxiv.org/abs/2510.08461 https://

Refinement-based Christoffel sampling for least squares approximation in non-orthogonal bases
We introduce a refinement-based Christoffel sampling (RCS) algorithm for least squares approximation in the span of a given, generally non-orthogonal set of functions $Φ_n = \{ϕ_1, \dots, ϕ_n\}$. A standard sampling strategy for this problem is Christoffel sampling, which achieves near-best approximations in probability using only $\mathcal{O}(n \log(n))$ samples. However, it requires i.i.d.\ sampling from a distribution whose density is proportional to the inverse Christoffel function $k_n$…

Synthetic Series-Symbol Data Generation for Time Series Foundation Models
Wenxuan Wang, Kai Wu, Yujian Betterest Li, Dan Wang, Xiaoyu Zhang
https://arxiv.org/abs/2510.08445 http…

Synthetic Series-Symbol Data Generation for Time Series Foundation Models
Foundation models for time series analysis (TSA) have attracted significant attention. However, challenges such as training data scarcity and imbalance continue to hinder their development. Inspired by complex dynamic system theories, we design a series-symbol data generation mechanism, enabling the unrestricted creation of high-quality time series data paired with corresponding symbolic expressions. To leverage series-symbol data pairs with strong correlations, we develop \texttt{SymTime}, a p…