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Queens Of The Stone Age:
🎵 No One Knows
#NowPlaying #QueensOfTheStoneAge
https://achokarlos.bandcamp.com/track/queens-of-the-stone-age-no-one-knows-feat-josh-steffen
https://open.spotify.com/track/6y20BV5L33R8YXM0YuI38N

Queueing for Civility: User Perspectives on Regulating Emotions in Online Conversations
Akriti Verma, Shama Islam, Valeh Moghaddam, Adnan Anwar
https://arxiv.org/abs/2507.11477

Queueing for Civility: User Perspectives on Regulating Emotions in Online Conversations
Online conversations are often interrupted by trolling, which causes emotional distress and conflict among users. Previous research has focused on moderating harmful content after it has been posted, but ways to manage emotions in real-time remain unexplored. This study suggests a comment queuing mechanism that delays comment publishing, encourages self-reflection, and reduces the impact of impulsive and toxic comments. To assess the efficacy of this approach, a mixed-method research design is …

Watermarking Quantum Neural Networks Based on Sample Grouped and Paired Training
Limengnan Zhou, Hanzhou Wu
https://arxiv.org/abs/2506.12675 https://

Watermarking Quantum Neural Networks Based on Sample Grouped and Paired Training
Quantum neural networks (QNNs) leverage quantum computing to create powerful and efficient artificial intelligence models capable of solving complex problems significantly faster than traditional computers. With the fast development of quantum hardware technology, such as superconducting qubits, trapped ions, and integrated photonics, quantum computers may become reality, accelerating the applications of QNNs. However, preparing quantum circuits and optimizing parameters for QNNs require quantu…

Analyzing Black-Hole Ringdowns with Orthonormal Modes
Soichiro Morisaki, Hayato Motohashi, Motoki Suzuki, Daiki Watarai
https://arxiv.org/abs/2507.12376 ht…

Analyzing Black-Hole Ringdowns with Orthonormal Modes
The ringdown signal following a BH merger can be modeled as a superposition of BH QNMs, offering a clean setup for testing gravitational theories. In particular, detecting multiple QNMs enables consistency checks of their frequencies and damping times, serving as a test of General Relativity -- a technique known as black hole spectroscopy. However, incorporating additional QNMs introduces challenges such as increased parameter correlations and higher computational costs in data analysis. To add…

Quantum quenches with long range interactions
Marianna Sorba, Nicol\`o Defenu, Gesualdo Delfino
https://arxiv.org/abs/2506.11617 https://

Quantum quenches with long range interactions
We extend the theory of quantum quenches to the case of $d$-dimensional homogeneous systems with long range interactions. This is achieved treating the long range interactions as switched on by the quench and performing the derivation within the basis of asymptotic states of the short range interacting pre-quench theory. In this way we analytically determine the post-quench state and the one-point functions of local observables such as the order parameter. One implication is that, as in the sho…

Thought Purity: Defense Paradigm For Chain-of-Thought Attack
Zihao Xue, Zhen Bi, Long Ma, Zhenlin Hu, Yan Wang, Zhenfang Liu, Qing Sheng, Jie Xiao, Jungang Lou
https://arxiv.org/abs/2507.12314

Thought Purity: Defense Paradigm For Chain-of-Thought Attack
While reinforcement learning-trained Large Reasoning Models (LRMs, e.g., Deepseek-R1) demonstrate advanced reasoning capabilities in the evolving Large Language Models (LLMs) domain, their susceptibility to security threats remains a critical vulnerability. This weakness is particularly evident in Chain-of-Thought (CoT) generation processes, where adversarial methods like backdoor prompt attacks can systematically subvert the model's core reasoning mechanisms. The emerging Chain-of-Thought Atta…

Enhancing Safe and Controllable Protein Generation via Knowledge Preference Optimization
Yuhao Wang, Keyan Ding, Kehua Feng, Zeyuan Wang, Ming Qin, Xiaotong Li, Qiang Zhang, Huajun Chen
https://arxiv.org/abs/2507.10923

Enhancing Safe and Controllable Protein Generation via Knowledge Preference Optimization
Protein language models have emerged as powerful tools for sequence generation, offering substantial advantages in functional optimization and denovo design. However, these models also present significant risks of generating harmful protein sequences, such as those that enhance viral transmissibility or evade immune responses. These concerns underscore critical biosafety and ethical challenges. To address these issues, we propose a Knowledge-guided Preference Optimization (KPO) framework that i…

🇺🇦 #NowPlaying on KEXP's #VarietyMix
KOLA:
🎵 Last Time
#KOLA
https://open.spotify.com/track/2QcmaHxFFZ1zkPwbpb7dVX

Finite-correlation-secure quantum key distribution
Yang-Guang Shan, Jia-Xuan Li, Zhen-Qiang Yin, Shuang Wang, Wei Chen, De-Yong He, Guang-Can Guo, Zheng-Fu Han
https://arxiv.org/abs/2507.11243

Finite-correlation-secure quantum key distribution
Correlation between different pulses is a nettlesome problem in quantum key distribution (QKD). All existing solutions for this problem need to characterize the strength of the correlation, which may reduce the security of QKD to an accurate characterization. In this article, we propose a new protocol immune to all correlations of all dimensions, with the only requirements of non-entangled and finite-ranged correlation, and bounded vacuum probability. Additionally, the new protocol is side-chan…

Toward Safety-First Human-Like Decision Making for Autonomous Vehicles in Time-Varying Traffic Flow
Xiao Wang, Junru Yu, Jun Huang, Qiong Wu, Ljubo Vacic, Changyin Sun
https://arxiv.org/abs/2506.14502

Toward Safety-First Human-Like Decision Making for Autonomous Vehicles in Time-Varying Traffic Flow
Despite the recent advancements in artificial intelligence technologies have shown great potential in improving transport efficiency and safety, autonomous vehicles(AVs) still face great challenge of driving in time-varying traffic flow, especially in dense and interactive situations. Meanwhile, human have free wills and usually do not make the same decisions even situate in the exactly same scenarios, leading to the data-driven methods suffer from poor migratability and high search cost proble…