Tootfinder

Apropos of nothing, here is #XKCD 1357.
#FreeSpeech

Large Language Model Prompt Datasets: An In-depth Analysis and Insights
Yuanming Zhang, Yan Lin, Arijit Khan, Huaiyu Wan
https://arxiv.org/abs/2510.09316 https://

Large Language Model Prompt Datasets: An In-depth Analysis and Insights
A prompt is a natural language instruction that defines a specific task for a large language model (LLM) and serves as the primary interface for human-LLM interaction. With the growing deployment of LLMs, diverse prompt datasets are emerging from platforms such as GitHub and social media. These datasets span a wide array of applications and content types, facilitating both broader LLM utilization and improved prompt engineering. In this work, we--for the first time--have compiled an extensive l…

Fast CZ Gate via Energy-Level Engineering in Superconducting Qubits with a Tunable Coupler
Benzheng Yuan, Chaojie Zhang, Chuanbing Han, Shuya Wang, Peng Xu, Huihui Sun, Qing Mu, Lixin Wang, Bo Zhao, Weilong Wang, Zheng Shan
https://arxiv.org/abs/2510.09461

Fast CZ Gate via Energy-Level Engineering in Superconducting Qubits with a Tunable Coupler
In superconducting quantum circuits, decoherence errors in qubits constitute a critical factor limiting quantum gate performance. To mitigate decoherence-induced gate infidelity, rapid implementation of quantum gates is essential. Here we propose a scheme for rapid controlled-Z (CZ) gate implementation through energy-level engineering, which leverages Rabi oscillations between the |11> state and the superposition state in a tunable-coupler architecture. Numerical simulations achieved a 17 …

Absolute clown show.
> In the encounter, which Murton filmed, an officer told her: “Mentioning freedom of Gaza, Israel, genocide, all of that all come under proscribed groups, which are terror groups that have been dictated by the government.”
https://www.the…

Generating Query-Relevant Document Summaries via Reinforcement Learning
Nitin Yadav, Changsung Kang, Hongwei Shang, Ming Sun
https://arxiv.org/abs/2508.08404 https://

Generating Query-Relevant Document Summaries via Reinforcement Learning
E-commerce search engines often rely solely on product titles as input for ranking models with latency constraints. However, this approach can result in suboptimal relevance predictions, as product titles often lack sufficient detail to capture query intent. While product descriptions provide richer information, their verbosity and length make them unsuitable for real-time ranking, particularly for computationally expensive architectures like cross-encoder ranking models. To address this challe…

HERO: Hardware-Efficient RL-based Optimization Framework for NeRF Quantization
Yipu Zhang, Chaofang Ma, Jinming Ge, Lin Jiang, Jiang Xu, Wei Zhang
https://arxiv.org/abs/2510.09010

HERO: Hardware-Efficient RL-based Optimization Framework for NeRF Quantization
Neural Radiance Field (NeRF) has emerged as a promising 3D reconstruction method, delivering high-quality results for AR/VR applications. While quantization methods and hardware accelerators have been proposed to enhance NeRF's computational efficiency, existing approaches face crucial limitations. Current quantization methods operate without considering hardware architecture, resulting in sub-optimal solutions within the vast design space encompassing accuracy, latency, and model size. Additio…

Optical emission from luminous and very soft X-ray sources in nearby galaxies: testing the scenario of edge-on supercritical accretion systems
Xiaohong Tang, Hua Feng
https://arxiv.org/abs/2508.08553

Optical emission from luminous and very soft X-ray sources in nearby galaxies: testing the scenario of edge-on supercritical accretion systems
Supercritical accretion onto compact objects is expected to drive optically thick winds, resulting in observed X-ray emission as a function of viewing angle. However, their optical emission, either from the outer accretion disk or companion surface tends to be nearly isotropic. Based on a sample of luminous and very soft X-ray sources that are argued to be supercritical accretion systems viewed close to edge-on, we identified the optical counterparts for some of them and compared the optical pr…

6G Resilience -- White Paper
Hirley Alves, Nurul H. Mahmood, Onel L. A. L\'opez, Sumudu Samarakoon, Seppo Yrj\"ol\"a, Matti Latva-Aho, Markku Juntti, Ari Pouttu, Armin Dekorsy, Arthur Sousa de Sena, Aydin Sezgin, Bho Matthiesen, Chafika Benzaid, Chathuranga Weeraddana, David Hutchison, Dileepa Marasinghe, Doganalp Ergenc, Eduard Jorswieck, Erkki Harjula, Falko Dressler, Harri Saarnisaari, Italo Atzeni, Jaap Van De Beek, Jacek Rak, Konstantin Mikhaylov, Lauri Loven, Madhus…

6G Resilience -- White Paper
6G must be designed to withstand, adapt to, and evolve amid prolonged, complex disruptions. Mobile networks' shift from efficiency-first to sustainability-aware has motivated this white paper to assert that resilience is a primary design goal, alongside sustainability and efficiency, encompassing technology, architecture, and economics. We promote resilience by analysing dependencies between mobile networks and other critical systems, such as energy, transport, and emergency services, and illus…

Unveiling Mechanical Motions in Non-linear Optical Organic Micro Ring Resonators
Melchi Chosenyah, Swaraj Rajaram, Vladimir Novikov, Anton Maydykovskiy, Ankur Khapre, Tatiana Murzina, Rajadurai Chandrasekar
https://arxiv.org/abs/2509.09228

Unveiling Mechanical Motions in Non-linear Optical Organic Micro Ring Resonators
This work demonstrates the multifaceted dynamic motion and three-dimensional (3D) spatial manipulation of organic micro ring resonators (MRRs). The MRRs are fabricated via surface-tension-assisted self-assembly of 2,2'-((1E,1'E)-hydrazine-1,2-diylidenebis(methaneylylidene))bis(3,5-dibromophenol) (HDBP), exhibiting nonlinear optical (NLO) emission and frequency comb-type whispering gallery modes. Interestingly, the MRRs are micromechanically reconfigurable into various strained architectures, in…

Quantum-centric simulation of hydrogen abstraction by sample-based quantum diagonalization and entanglement forging
Tyler Smith, Tanvi P. Gujarati, Mario Motta, Ben Link, Ieva Liepuoniute, Triet Friedhoff, Hiromichi Nishimura, Nam Nguyen, Kristen S. Williams, Javier Robledo Moreno, Caleb Johnson, Kevin J. Sung, Abdullah Ash Saki, Marna Kagele
https://

Quantum-centric simulation of hydrogen abstraction by sample-based quantum diagonalization and entanglement forging
The simulation of electronic systems is an anticipated application for quantum-centric computers, i.e. heterogeneous architectures where classical and quantum processing units operate in concert. An important application is the computation of radical chain reactions, including those responsible for the photodegradation of composite materials used in aerospace engineering. Here, we compute the activation energy and reaction energy for hydrogen abstraction from 2,2-diphenyldipropane, used as a mi…