Kavli Affiliate: Irfan Siddiqi | First 5 Authors: Larry Chen, Kan-Heng Lee, Chuan-Hong Liu, Brian Marinelli, Ravi K. Naik | Summary: State-of-the-art superconducting quantum processors containing tens to hundreds of qubits have demonstrated the building blocks for realizing fault-tolerant quantum computation. Nonetheless, a fundamental barrier to scaling further is the prevalence of fluctuating quantum two-level […]

Kavli Affiliate: Graham Fleming | First 5 Authors: Yuping Shi, Partha Roy, Naoki Higashitarumizue, Tsung-Yen Lee, Quanwei Li | Summary: A combination of ultrafast, long-range and low-loss excitation energy transfer from the photo-receptor location to a functionally active site is essential for cost-effective polymeric semiconductors. Delocalized electronic wavefunctions along {pi}-conjugated polymer backbone can enable efficient […]

Kavli Affiliate: Xiang Zhang | First 5 Authors: Xiang Zhang, Zhou Li, Kai Wan, Hua Sun, Mingyue Ji | Summary: Secure aggregation is motivated by federated learning (FL) where a cloud server aims to compute an averaged model (i.e., weights of deep neural networks) of the locally-trained models of numerous clients, while adhering to data […]

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: 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: 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 […]