Tootfinder

Space-based mm/mg-scale Laser Interferometer for Quantum Gravity
Nobuyuki Matsumoto, Katsuta Sakai, Kosei Hatakeyama, Kiwamu Izumi, Daisuke Miki, Satoshi Iso, Akira Matsumura, Kazuhiro Yamamoto
https://arxiv.org/abs/2507.12899

Space-based mm/mg-scale Laser Interferometer for Quantum Gravity
The experimental verification of the quantum nature of gravity represents a milestone in quantum gravity research. Recently, interest has grown for testing it via gravitationally induced entanglement (GIE). Here, we propose a space-based interferometer inspired by the LISA Pathfinder (LPF). Unlike the LPF, our design employs two smaller gold-platinum test masses, each weighing the milligram scale, surrounded by a shield below 2 K, and positioned side by side with a millimeter scale separation. …

interessanter #trick für #PowerPoint:
"Textstellen in PowerPoint mit dem Textmarker hervorheben – jetzt mit individuellen Farben"

Unter den von der israelischen Armee festgenommenen Aktivist:innen befindet sich auch die deutsche Staatsbürgerin Yasemin Acar. Wir müssen jetzt Druck aufbauen um für ihre Freilassung zu kämpfen!
Dies ist ein Kidnapping. Das israelische Militär hat kein Recht auf internationalen Gewässern Menschen festzunehmen und ist auch keine rechtliche Repräsentation für den Gazastreifen. Hier wird ein Land mal wieder mit etwas durchkommen was höchstgradig illegal ist!

WAS Z…

Deutscher Bundestag - Abgeordnete
Eine Übersicht über die gewählten Abgeordneten des Deutschen Bundestages, die Wahlkreise und Informationen über Tätigkeiten sowie Einkünfte, Pauschalen und Sachleistungen.

Verification of the Release-Acquire Semantics
Parosh Abdulla, Elli Anastasiadi, Mohamed Faouzi Atig, Samuel Grahn
https://arxiv.org/abs/2506.08238 https://…

Verification of the Release-Acquire Semantics
The Release-Acquire (RA) semantics and its variants are some of the most fundamental models of concurrent semantics for architectures, programming languages, and distributed systems. Several steps have been taken in the direction of testing such semantics, where one is interested in whether a single program execution is consistent with a memory model. The more general verification problem, i.e., checking whether all allowed program runs are consistent with a memory model, has still not been stu…

ASSURE: Metamorphic Testing for AI-powered Browser Extensions
Xuanqi Gao, Juan Zhai, Shiqing Ma, Siyi Xie, Chao Shen
https://arxiv.org/abs/2507.05307 https…

ASSURE: Metamorphic Testing for AI-powered Browser Extensions
The integration of Large Language Models (LLMs) into browser extensions has revolutionized web browsing, enabling sophisticated functionalities like content summarization, intelligent translation, and context-aware writing assistance. However, these AI-powered extensions introduce unprecedented challenges in testing and reliability assurance. Traditional browser extension testing approaches fail to address the non-deterministic behavior, context-sensitivity, and complex web environment integrat…

Esoteric Language Models
Subham Sekhar Sahoo, Zhihan Yang, Yash Akhauri, Johnna Liu, Deepansha Singh, Zhoujun Cheng, Zhengzhong Liu, Eric Xing, John Thickstun, Arash Vahdat
https://arxiv.org/abs/2506.01928

Esoteric Language Models
Diffusion-based language models offer a compelling alternative to autoregressive (AR) models by enabling parallel and controllable generation. Among this family of models, Masked Diffusion Models (MDMs) achieve the strongest performance but still underperform AR models in perplexity and lack key inference-time efficiency features--most notably, KV caching. In this work, we introduce Eso-LMs, a new family of models that fuses AR and MDM paradigms, enabling smooth interpolation between their perp…

Testing the ubiquitous presence of very high energy emission in gamma-ray bursts with the MAGIC telescopes
S. Abe, J. Abhir, A. Abhishek, V. A. Acciari, A. Aguasca-Cabot, I. Agudo, T. Aniello, S. Ansoldi, L. A. Antonelli, A. Arbet Engels, C. Arcaro, T. T. H. Arnesen, K. Asano, A. Babic, C. Bakshi, U. Barres de Almeida, J. A. Barrio, L. Barrios-Jimenez, I. Batkovic, J. Baxter, J. Becerra Gonzalez, W. Bednarek, E. Bernardini, J. Bernete, A. Berti, J. Besenrieder, C. Bigongiari, A. Biland…

Testing the ubiquitous presence of very high energy emission in gamma-ray bursts with the MAGIC telescopes
Gamma-ray bursts (GRBs) are the most powerful transient objects in the Universe, and they are a primary target for the MAGIC Collaboration. Recognizing the challenges of observing these elusive objects with Imaging Atmospheric Cherenkov Telescopes (IACTs), we implemented a dedicated observational strategy that included an automated procedure for rapid re-pointing to transient sources. Since 2013, this automated procedure has enabled MAGIC to observe GRBs at a rate of approximately ten per year,…

Leveraging Correlation Across Test Platforms for Variance-Reduced Metric Estimation
Rachel Luo, Heng Yang, Michael Watson, Apoorva Sharma, Sushant Veer, Edward Schmerling, Marco Pavone
https://arxiv.org/abs/2506.20553

Leveraging Correlation Across Test Platforms for Variance-Reduced Metric Estimation
Learning-based robotic systems demand rigorous validation to assure reliable performance, but extensive real-world testing is often prohibitively expensive, and if conducted may still yield insufficient data for high-confidence guarantees. In this work, we introduce a general estimation framework that leverages paired data across test platforms, e.g., paired simulation and real-world observations, to achieve better estimates of real-world metrics via the method of control variates. By incorpora…

Leveraging In-Context Learning for Political Bias Testing of LLMs
Patrick Haller, Jannis Vamvas, Rico Sennrich, Lena A. J\"ager
https://arxiv.org/abs/2506.22232

Leveraging In-Context Learning for Political Bias Testing of LLMs
A growing body of work has been querying LLMs with political questions to evaluate their potential biases. However, this probing method has limited stability, making comparisons between models unreliable. In this paper, we argue that LLMs need more context. We propose a new probing task, Questionnaire Modeling (QM), that uses human survey data as in-context examples. We show that QM improves the stability of question-based bias evaluation, and demonstrate that it may be used to compare instruct…

Replaced article(s) found for econ.GN. https://arxiv.org/list/econ.GN/new
[1/1]:
- Optimal taxation and the Domar-Musgrave effect
Brendan K. Beare, Alexis Akira Toda