Tootfinder

Atomic Observables Induced by Cosmic Fields
Sebastian Lahs, Daniel Comparat, Fiona Kirk, Benjamin Roberts
https://arxiv.org/abs/2510.08007 https://arxiv.or…

Atomic Observables Induced by Cosmic Fields
The existence of cosmic fields made from yet unknown light bosons is predicted in many extensions to the Standard Model. They are especially of interest as possible constituents of dark matter. To detect such light and weakly interacting fields, atomic precision measurements offer one of the most sensitive platforms. In this work, we derive which atomic observables are sensitive to what kind of cosmic field couplings. For this we consider fields that couple either through scalar, pseudoscalar, …

The Alignment Waltz: Jointly Training Agents to Collaborate for Safety
Jingyu Zhang, Haozhu Wang, Eric Michael Smith, Sid Wang, Amr Sharaf, Mahesh Pasupuleti, Benjamin Van Durme, Daniel Khashabi, Jason Weston, Hongyuan Zhan
https://arxiv.org/abs/2510.08240

The Alignment Waltz: Jointly Training Agents to Collaborate for Safety
Harnessing the power of LLMs requires a delicate dance between being helpful and harmless. This creates a fundamental tension between two competing challenges: vulnerability to adversarial attacks that elicit unsafe content, and a tendency for overrefusal on benign but sensitive prompts. Current approaches often navigate this dance with safeguard models that completely reject any content that contains unsafe portions. This approach cuts the music entirely-it may exacerbate overrefusals and fail…

VersionRAG: Version-Aware Retrieval-Augmented Generation for Evolving Documents
Daniel Huwiler, Kurt Stockinger, Jonathan F\"urst
https://arxiv.org/abs/2510.08109 https://

VersionRAG: Version-Aware Retrieval-Augmented Generation for Evolving Documents
Retrieval-Augmented Generation (RAG) systems fail when documents evolve through versioning-a ubiquitous characteristic of technical documentation. Existing approaches achieve only 58-64% accuracy on version-sensitive questions, retrieving semantically similar content without temporal validity checks. We present VersionRAG, a version-aware RAG framework that explicitly models document evolution through a hierarchical graph structure capturing version sequences, content boundaries, and changes be…

Learning to accelerate distributed ADMM using graph neural networks
Henri Doerks, Paul H\"ausner, Daniel Hern\'andez Escobar, Jens Sj\"olund
https://arxiv.org/abs/2509.05288

Learning to accelerate distributed ADMM using graph neural networks
Distributed optimization is fundamental in large-scale machine learning and control applications. Among existing methods, the Alternating Direction Method of Multipliers (ADMM) has gained popularity due to its strong convergence guarantees and suitability for decentralized computation. However, ADMM often suffers from slow convergence and sensitivity to hyperparameter choices. In this work, we show that distributed ADMM iterations can be naturally represented within the message-passing framewor…

wow the only person who brought up Sunset Dunes/the former Great Highway at Lurie's D4 listening tour was someone who supports the park.
https://missionlocal.org/2025/09/sf-mayor-daniel-lurie-listening-sunset/

Lurie, in Sunset ‘listening mode,’ says he’ll tap a supe for the long haul
Daniel Lurie asks merchants, recall leaders and community groups who they want to represent them, and talks about upzoning

Predicting Market Troughs: A Machine Learning Approach with Causal Interpretation
Peilin Rao, Randall R. Rojas
https://arxiv.org/abs/2509.05922 https://arx…

Predicting Market Troughs: A Machine Learning Approach with Causal Interpretation
This paper provides robust, new evidence on the causal drivers of market troughs. We demonstrate that conclusions about these triggers are critically sensitive to model specification, moving beyond restrictive linear models with a flexible DML average partial effect causal machine learning framework. Our robust estimates identify the volatility of options-implied risk appetite and market liquidity as key causal drivers, relationships misrepresented or obscured by simpler models. These findings …

The evolution of insurance purchasing behavior: an empirical study on the adoption of online channels in Poland
Gabriela Wojak, Ernest G\'orka, Micha{\l} \'Cwi\k{a}ka{\l}a, Dariusz Baran, Rafa{\l} \'Swiniarski, Katarzyna Olszy\'nska, Piotr Mrzyg{\l}\'od, Maciej Frasunkiewicz, Piotr R\k{e}czajski, Daniel Zawadzki, Jan Piwnik
https://

The evolution of insurance purchasing behavior: an empirical study on the adoption of online channels in Poland
This paper examines how Polish consumers are adapting to online insurance purchasing channels and what factors influence their preferences. Drawing on a structured survey of 100 respondents with varied demographic profiles, the study explores purchasing frequency, channel usage, price sensitivity, trust, and decision-making behaviors. Results indicate a clear shift toward digital tools, with many consumers valuing the speed, convenience, and transparency of online platforms, particularly for si…

A scalable method for cavity-enhanced solid-state quantum sensors
Daniel J. Tibben, Roy Styles, David A. Broadway, Jean-Philippe Tetienne, Daniel E. G\'omez, Philipp Reineck
https://arxiv.org/abs/2509.04760

A scalable method for cavity-enhanced solid-state quantum sensors
Photoluminescent color centers in diamond and hexagonal boron nitride (hBN) are powerful nanoscale solid-state quantum sensors that are explored in a plethora of quantum technologies. Methods for integrating them into macroscopic structures that improve their sensitivity and enable their large-scale deployment are highly sought after. Here, we demonstrate cavity-enhanced photoluminescence (PL) of fluorescent nanodiamonds (FNDs) and hBN nanoparticles (NPs) embedded in polymer-based thin-film opt…

Backing the Wrong Horse: How Bit-Level Netlist Augmentation can Counter Power Side Channel Attacks
Ali Asghar, Andreas Becher, Daniel Ziener
https://arxiv.org/abs/2510.04640 htt…

Backing the Wrong Horse: How Bit-Level Netlist Augmentation can Counter Power Side Channel Attacks
The dependence of power-consumption on the processed data is a known vulnerability of CMOS circuits, resulting in side channels which can be exploited by power-based side channel attacks (SCAs). These attacks can extract sensitive information, such as secret keys, from the implementation of cryptographic algorithms. Existing countermeasures against power-based side channel attacks focus on analyzing information leakage at the byte level. However, this approach neglects the impact of individual …

Advances in Radiative Capture Studies at LUNA with a Segmented BGO Detector
Jakub Skowronski, Riccardo Maria Gesu\`e, Axel Boeltzig, Giovanni Francesco Ciani, Denise Piatti, David Rapagnani, Marialuisa Aliotta, Chemsedinne Ananna, Francesco Barile, Daniel Bemmerer, Andreas Best, Carlo Broggini, Carlo Giovanni Bruno, Antonio Caciolli, Matteo Campostrini, Francesca Cavanna, Paolo Colombetti, Alessandro Compagnucci, Piero Corvisiero, Laszlo Csedreki, Tom Davinson, Rosanna Depalo, Antonino…

Advances in Radiative Capture Studies at LUNA with a Segmented BGO Detector
Studies of charged-particle reactions for low-energy nuclear astrophysics require high sensitivity, which can be achieved by means of detection setups with high efficiency and low backgrounds, to obtain precise measurements in the energy region of interest for stellar scenarios. High-efficiency total absorption spectroscopy is an established and powerful tool for studying radiative capture reactions, particularly if combined with the cosmic background reduction by several orders of magnitude ob…