Kavli Affiliate: Kristin A. Persson | First 5 Authors: Aaron D. Kaplan, Runze Liu, Ji Qi, Tsz Wai Ko, Bowen Deng | Summary: Accurate potential energy surface (PES) descriptions are essential for atomistic simulations of materials. Universal machine learning interatomic potentials (UMLIPs)$^{1-3}$ offer a computationally efficient alternative to density functional theory (DFT)$^4$ for PES modeling […]
Kavli Affiliate: Katja C. Nowack | First 5 Authors: George M. Ferguson, Run Xiao, Anthony R. Richardella, Austin Kaczmarek, Nitin Samarth | Summary: The creation of topologically non-trivial matter across electronic, mechanical, cold-atom, and photonic platforms is advancing rapidly, yet understanding the breakdown of topological protection remains a major challenge. In this work, we use […]
Kavli Affiliate: Ting Xu | First 5 Authors: Ran Hao, Yanlin Xiang, Junliang Du, Qingyuan He, Jiacheng Hu | Summary: This study proposed a hybrid model of a convolutional neural network (CNN) and a Transformer to predict and diagnose heart disease. Based on CNN’s strength in detecting local features and the Transformer’s high capacity in […]
Kavli Affiliate: Feng Wang | First 5 Authors: Feng Wang, Zesheng Shi, Bo Wang, Nan Wang, Han Xiao | Summary: We present ReaderLM-v2, a compact 1.5 billion parameter language model designed for efficient web content extraction. Our model processes documents up to 512K tokens, transforming messy HTML into clean Markdown or JSON formats with high […]
Kavli Affiliate: Morteza Gharib | First 5 Authors: Ioannis Mandralis, Reza Nemovi, Alireza Ramezani, Richard M. Murray, Morteza Gharib | Summary: Designing ground-aerial robots is challenging due to the increased actuation requirements which can lead to added weight and reduced locomotion efficiency. Morphobots mitigate this by combining actuators into multi-functional groups and leveraging ground transformation […]
Kavli Affiliate: Irfan Siddiqi | First 5 Authors: Luca Spagnoli, Noah Goss, Alessandro Roggero, Ermal Rrapaj, Michael J. Cervia | Summary: Collective neutrino flavor oscillations are of primary importance in understanding the dynamic evolution of core-collapse supernovae and subsequent terrestrial detection, but also among the most challenging aspects of numerical simulations. This situation is complicated […]
Kavli Affiliate: Irfan Siddiqi | First 5 Authors: Luca Spagnoli, Noah Goss, Alessandro Roggero, Ermal Rrapaj, Michael J. Cervia | Summary: Collective neutrino flavor oscillations are of primary importance in understanding the dynamic evolution of core-collapse supernovae and subsequent terrestrial detection, but also among the most challenging aspects of numerical simulations. This situation is complicated […]
Kavli Affiliate: Kristin A. Persson | First 5 Authors: Jingru Gan, Peichen Zhong, Yuanqi Du, Yanqiao Zhu, Chenru Duan | Summary: Crystal structure generation is fundamental to materials discovery, enabling the prediction of novel materials with desired properties. While existing approaches leverage Large Language Models (LLMs) through extensive fine-tuning on materials databases, we show that […]
Kavli Affiliate: Xiang Zhang | First 5 Authors: Juntai Cao, Xiang Zhang, Raymond Li, Chuyuan Li, Shafiq Joty | Summary: Recent advances in test-time scaling have shown promising results in improving Large Language Models (LLMs) performance through strategic computation allocation during inference. While this approach has demonstrated strong performance improvements in logical and mathematical reasoning […]
Kavli Affiliate: Stephanie Wehner | First 5 Authors: Álvaro G. Iñesta, Bethany Davies, Sounak Kar, Stephanie Wehner, | Summary: Entanglement buffers are systems that maintain high-quality entanglement, ensuring it is readily available for consumption when needed. In this work, we study the performance of a two-node buffer, where each node has one long-lived quantum memory […]