Tootfinder

Two new NERDS papers published at CHIIR 2025
https://nerds.itu.dk/2025/05/02/two-new-nerds-papers-published-at-chiir-2025/

This is an interesting article about FFOTUS's cell phone.
Apparently many people know the number. And apparently FFOTUS often picks up and answers.
If I had the number I would publish it so that all of us could carry out our First Amendment right to "right to petition the government for redress of grievances".
"The Secret History of Trump’s Private Cellphone"

The Secret History of Trump’s Private Cellphone
“Who’s calling?” the president asks as he answers call after call from numbers he doesn’t know.

Charge Regulation Effect on Nanoparticles Interaction Mediated by Polyelectrolyte
Vijay Yadav, Prabhat Kumar Jaiswal, Rudolf Podgornik, Sunita Kumari
https://arxiv.org/abs/2507.00549

Charge Regulation Effect on Nanoparticles Interaction Mediated by Polyelectrolyte
The ability to precisely control surface charge using charged polymers is fundamental to many nanotechnology applications, enabling the design and fabrication of materials with tailored properties and functionalities. Here, we study the effect of charge regulation (CR) on the interaction between two nanoparticles (NPs) mediated by an oppositely charged polyelectrolyte (PE) in an electrolyte solution. To this end, we employ a hybrid CR Monte Carlo (CR-MC)/molecular dynamics (MD) simulation frame…

This https://arxiv.org/abs/2403.11981 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

Certified Robustness to Clean-Label Poisoning Using Diffusion Denoising
We present a certified defense to clean-label poisoning attacks under $\ell_2$-norm. These attacks work by injecting a small number of poisoning samples (e.g., 1%) that contain bounded adversarial perturbations into the training data to induce a targeted misclassification of a test-time input. Inspired by the adversarial robustness achieved by $randomized$ $smoothing$, we show how an off-the-shelf diffusion denoising model can sanitize the tampered training data. We extensively test our defense…

This https://arxiv.org/abs/2505.09795 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIR_…

Beyond Pairwise Learning-To-Rank At Airbnb
There are three fundamental asks from a ranking algorithm: it should scale to handle a large number of items, sort items accurately by their utility, and impose a total order on the items for logical consistency. But here's the catch-no algorithm can achieve all three at the same time. We call this limitation the SAT theorem for ranking algorithms. Given the dilemma, how can we design a practical system that meets user needs? Our current work at Airbnb provides an answer, with a working solutio…

Drift, diffusion and divergence
Laurette S. Tuckerman
https://arxiv.org/abs/2506.00621 https://arxiv.org/pdf/2506.00621

Drift, diffusion and divergence
Turbulent Taylor-Couette flow displays traces of axisymmetric Taylor vortices even at high Reynolds numbers. With this motivation, Feldmann & Avila (2025) carry out long-time numerical simulations of axisymmetric high-Reynolds-number Taylor-Couette flow. They find that the Taylor vortices, using the only degree of freedom that remains available to them, carry out Brownian motion in the axial direction, with a diffusion constant that diverges as the number of rolls is reduced below a critical va…

This https://arxiv.org/abs/2406.14567 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csGR_…

DragPoser: Motion Reconstruction from Variable Sparse Tracking Signals via Latent Space Optimization
High-quality motion reconstruction that follows the user's movements can be achieved by high-end mocap systems with many sensors. However, obtaining such animation quality with fewer input devices is gaining popularity as it brings mocap closer to the general public. The main challenges include the loss of end-effector accuracy in learning-based approaches, or the lack of naturalness and smoothness in IK-based solutions. In addition, such systems are often finely tuned to a specific number of t…

Die Stadt #BadWünnenberg verlängert ihr #Förderprogramm für #Klimaschutz bis Ende 2025.
Bürgerinnen und Bürger erhalten bis zu 2.500 Euro für Maßnahmen wie

Stadt Bad Wünnenberg verlängert Förderprogramm für Klimaschutzmaßnahmen - Bad Wünnenberg
Auch im Jahr 2025 unterstützt die Stadt Bad Wünnenberg gezielt Maßnahmen zum Klimaschutz. Insgesamt stehen erneut 25.000 Euro zur Verfügung, um Bürgerinnen und Bürger zu motivieren, aktiv zur Reduzierung von Treibhausgasen und zur Anpassung an die Folgen des Klimawandels beizutragen. Die Förderrichtlinie wurde überarbeitet und inhaltlich erweitert – unter anderem wurde der Zuschuss für Gründächer und Fassadenbegrünung auf 20 Euro pro Quadratmeter erhöht.

This https://arxiv.org/abs/2405.12042 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

Attribute-Based Authentication in Secure Group Messaging for Distributed Environments
Messaging Layer security (MLS) and its underlying Continuous Group Key Agreement (CGKA) protocol allows a group of users to share a cryptographic secret in a dynamic manner, such that the secret is modified in member insertions and deletions. Although this flexibility makes MLS ideal for implementations in distributed environments, a number of issues need to be overcome. Particularly, the use of digital certificates for authentication in a group goes against the group members' privacy. In this …

AI-Hybrid TRNG: Kernel-Based Deep Learning for Near-Uniform Entropy Harvesting from Physical Noise
Hasan Yi\u{g}it
https://arxiv.org/abs/2507.00145 https:/…

AI-Hybrid TRNG: Kernel-Based Deep Learning for Near-Uniform Entropy Harvesting from Physical Noise
AI-Hybrid TRNG is a deep-learning framework that extracts near-uniform entropy directly from physical noise, eliminating the need for bulky quantum devices or expensive laboratory-grade RF receivers. Instead, it relies on a low-cost, thumb-sized RF front end, plus CPU-timing jitter, for training, and then emits 32-bit high-entropy streams without any quantization step. Unlike deterministic or trained artificial intelligence random number generators (RNGs), our dynamic inner-outer network coup…