Tootfinder

Unavoidable butterfly minors in digraphs of large cycle rank
Meike Hatzel, O-joung Kwon, Myounghwan Lee, Sebastian Wiederrecht
https://arxiv.org/abs/2507.11814

Unavoidable butterfly minors in digraphs of large cycle rank
Cycle rank is one of the depth parameters for digraphs introduced by Eggan in 1963. We show that there exists a function $f:\mathbb{N}\to \mathbb{N}$ such that every digraph of cycle rank at least $f(k)$ contains a directed cycle chain, a directed ladder, or a directed tree chain of order $k$ as a butterfly minor. We also investigate a new connection between cycle rank and a directed analogue of the weak coloring number of graphs.

Private Memorization Editing: Turning Memorization into a Defense to Strengthen Data Privacy in Large Language Models
Elena Sofia Ruzzetti, Giancarlo A. Xompero, Davide Venditti, Fabio Massimo Zanzotto
https://arxiv.org/abs/2506.10024

Private Memorization Editing: Turning Memorization into a Defense to Strengthen Data Privacy in Large Language Models
Large Language Models (LLMs) memorize, and thus, among huge amounts of uncontrolled data, may memorize Personally Identifiable Information (PII), which should not be stored and, consequently, not leaked. In this paper, we introduce Private Memorization Editing (PME), an approach for preventing private data leakage that turns an apparent limitation, that is, the LLMs' memorization ability, into a powerful privacy defense strategy. While attacks against LLMs have been performed exploiting previou…

Safe-Child-LLM: A Developmental Benchmark for Evaluating LLM Safety in Child-AI Interactions
Junfeng Jiao, Saleh Afroogh, Kevin Chen, Abhejay Murali, David Atkinson, Amit Dhurandhar
https://arxiv.org/abs/2506.13510

Safe-Child-LLM: A Developmental Benchmark for Evaluating LLM Safety in Child-AI Interactions
As Large Language Models (LLMs) increasingly power applications used by children and adolescents, ensuring safe and age-appropriate interactions has become an urgent ethical imperative. Despite progress in AI safety, current evaluations predominantly focus on adults, neglecting the unique vulnerabilities of minors engaging with generative AI. We introduce Safe-Child-LLM, a comprehensive benchmark and dataset for systematically assessing LLM safety across two developmental stages: children (7-12…

Disentangling Boltzmann brains, the time-asymmetry of memory, the H theorem, and the second law
David Wolpert, Carlo Rovelli, Jordan Scharnhorst
https://arxiv.org/abs/2507.10959

Disentangling Boltzmann brains, the time-asymmetry of memory, the H theorem, and the second law
Are you, with your perceptions, memories and observational data, a Boltzmann brain, i.e., a statistical fluctuation out of the thermal equilibrium of the universe? Arguments are given in the literature for and against taking this hypothesis seriously. Complicating these analyses have been the many subtle - and very often implicit - entanglements between related arguments that have been given for the past hypothesis, the second law, and even Bayesian inference of the reliability of experimental …

Justice Dept. Demands Patient Details From Trans Medicine Providers (New York Times)
https://www.nytimes.com/2025/07/10/health/transgender-medicine-minors-trump-subpoena.html?unlocked_article_code=1.VU8.-jw7.Tu6IpFti68dH&smid=nytcore-ios-share&referringSource=articleShare
http://www.memeorandum.com/250710/p148#a250710p148

Preprocessing Methods for Memristive Reservoir Computing for Image Recognition
Rishona Daniels, Duna Wattad, Ronny Ronen, David Saad, Shahar Kvatinsky
https://arxiv.org/abs/2506.05588

Preprocessing Methods for Memristive Reservoir Computing for Image Recognition
Reservoir computing (RC) has attracted attention as an efficient recurrent neural network architecture due to its simplified training, requiring only its last perceptron readout layer to be trained. When implemented with memristors, RC systems benefit from their dynamic properties, which make them ideal for reservoir construction. However, achieving high performance in memristor-based RC remains challenging, as it critically depends on the input preprocessing method and reservoir size. Despite …

A scalable photonic quantum interconnect platform
Daniel Riedel, Teodoro Graziosi, Zhuoxian Wang, Chawina De-Eknamkul, Alex Abulnaga, Jonathan Dietz, Andrea Mucchietto, Michael Haas, Madison Sutula, Pierre Barral, Matteo Pompili, Carsten Robens, Jeonghoon Ha, Denis Sukachev, David Levonian, Mihir Bhaskar, Matthew Markham, Bartholomeus Machielse
https://

A scalable photonic quantum interconnect platform
Many quantum networking applications require efficient photonic interfaces to quantum memories which can be produced at scale and with high yield. Synthetic diamond offers unique potential for the implementation of this technology as it hosts color centers which retain coherent optical interfaces and long spin coherence times in nanophotonic structures. Here, we report a technique enabling wafer-scale processing of thin-film diamond that combines ion implantation and membrane liftoff, high-qual…

Nature of Data in Pre-Trained Large Language Models
https://fpf.org/blog/nature-of-data-in-pre-trained-large-language-models/
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Quantum State Preparation Of Multiconfigurational States For Quantum Chemistry
Gabriel Greene-Diniz, Georgia Prokopiou, David Zsolt Manrique, David Mu\~noz Ramo
https://arxiv.org/abs/2508.05390

Quantum State Preparation Of Multiconfigurational States For Quantum Chemistry
The ability to prepare states for quantum chemistry is a promising feature of quantum computers, and efficient techniques for chemical state preparation is an active area of research. In this paper, we implement and investigate two methods of quantum circuit preparation for multiconfigurational states for quantum chemical applications. It has previously been shown that controlled Givens rotations are universal for quantum chemistry. To prepare a selected linear combination of Slater determinant…

Unavoidable pivot-minors in graphs of large rank-depth
Jungho Ahn, Kevin Hendrey, O-joung Kwon, Sang-il Oum
https://arxiv.org/abs/2507.12697 https://

Unavoidable pivot-minors in graphs of large rank-depth
Shrub-depth and rank-depth are related graph parameters that are dense analogs of tree-depth. We prove that for every positive integer $t$, every graph of sufficiently large rank-depth contains a pivot-minor isomorphic to a path on $t$ vertices or a graph consisting of two disjoint cliques of size $t$ joined by a half graph. This answers an open problem raised by Kwon, McCarty, Oum, and Wollan in 2021.