Spectra-orthogonal optical anisotropy in wafer-scale molecular crystal monolayers

Kavli Affiliate: David A. Muller | First 5 Authors: Tomojit Chowdhury, Fauzia Mujid, Zehra Naqvi, Ariana Ray, Ce Liang | Summary: Controlling the spectral and polarization responses of two-dimensional (2D) crystals is vital for developing ultra-thin platforms for compact optoelectronic devices. However, independently tuning optical anisotropy and spectral response remains challenging in conventional semiconductors due […]


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Harmonic Loss Trains Interpretable AI Models

Kavli Affiliate: Max Tegmark | First 5 Authors: David D. Baek, Ziming Liu, Riya Tyagi, Max Tegmark, | Summary: In this paper, we introduce **harmonic loss** as an alternative to the standard cross-entropy loss for training neural networks and large language models (LLMs). Harmonic loss enables improved interpretability and faster convergence, owing to its scale […]


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Genetic Architecture and Analysis Practices of Circulating Metabolites in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program

Kavli Affiliate: V. S. Ramachandran | Authors: Nannan Wang, Franklin P. Ockerman, Laura Y. Zhou, Megan L Grove, Taryn Alkis, John Barnard, Russell P. Bowler, Clary B. Clish, Shinhye Chung, Emily Drzymalla, Anne M. Evans, Nora Franceschini, Robert E. Gerszten, Madeline G. Gillman, Scott R. Hutton, Rachel S. Kelly, Charles Kooperberg, Martin G. Larson, Jessica […]


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Two-particle quantum interference in a nonlinear optical medium: a witness of timelike indistinguishability

Kavli Affiliate: Jing Wang | First 5 Authors: Chao Chen, Shu-Tian Xue, Yu-Peng Shi, Jing Wang, Zi-Mo Cheng | Summary: The Hong-Ou-Mandel effect is a paradigmatic quantum phenomenon demonstrating the interference of two indistinguishable photons that are linearly coupled at a 50:50 beam splitter. Here, we transpose such a two-particle quantum interference effect to the […]


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Learning Fused State Representations for Control from Multi-View Observations

Kavli Affiliate: Li Xin Li | First 5 Authors: Zeyu Wang, Yao-Hui Li, Xin Li, Hongyu Zang, Romain Laroche | Summary: Multi-View Reinforcement Learning (MVRL) seeks to provide agents with multi-view observations, enabling them to perceive environment with greater effectiveness and precision. Recent advancements in MVRL focus on extracting latent representations from multiview observations and […]


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A practical Bayesian method for gravitational-wave ringdown analysis with multiple modes

Kavli Affiliate: Lijing Shao | First 5 Authors: Yiming Dong, Ziming Wang, Hai-Tian Wang, Junjie Zhao, Lijing Shao | Summary: Gravitational-wave (GW) ringdown signals from black holes (BHs) encode crucial information about the gravitational dynamics in the strong-field regime, which offers unique insights into BH properties. In the future, the improving sensitivity of GW detectors […]


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Population Representation of the Confidence in a Decision in the Parietal Cortex

Kavli Affiliate: Michael Shadlen | Authors: Ariel Zylberberg and Michael N Shadlen | Summary: Confidence in a decision is the belief, prior to feedback, that one’s choice is correct. In the brain, many decisions are implemented as a race between competing evidence-accumulation processes. We ask whether the neurons that represent evidence accumulation also carry information […]


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Language Models Use Trigonometry to Do Addition

Kavli Affiliate: Max Tegmark | First 5 Authors: Subhash Kantamneni, Max Tegmark, , , | Summary: Mathematical reasoning is an increasingly important indicator of large language model (LLM) capabilities, yet we lack understanding of how LLMs process even simple mathematical tasks. To address this, we reverse engineer how three mid-sized LLMs compute addition. We first […]


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Psychometric-Based Evaluation for Theorem Proving with Large Language Models

Kavli Affiliate: Long Zhang | First 5 Authors: Jianyu Zhang, Yongwang Zhao, Long Zhang, Jilin Hu, Xiaokun Luan | Summary: Large language models (LLMs) for formal theorem proving have become a prominent research focus. At present, the proving ability of these LLMs is mainly evaluated through proof pass rates on datasets such as miniF2F. However, […]


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Cosmological super-resolution of the 21-cm signal

Kavli Affiliate: George Efstathiou | First 5 Authors: Simon Pochinda, Jiten Dhandha, Anastasia Fialkov, Eloy de Lera Acedo, | Summary: In this study, we train score-based diffusion models to super-resolve gigaparsec-scale cosmological simulations of the 21-cm signal. We examine the impact of network and training dataset size on model performance, demonstrating that a single simulation […]


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