On the Impact of Cross-Domain Data on German Language Models

Kavli Affiliate: Cheng Peng | First 5 Authors: Amin Dada, Aokun Chen, Cheng Peng, Kaleb E Smith, Ahmad Idrissi-Yaghir | Summary: Traditionally, large language models have been either trained on general web crawls or domain-specific data. However, recent successes of generative large language models, have shed light on the benefits of cross-domain datasets. To examine […]


Continue.. On the Impact of Cross-Domain Data on German Language Models

On the Impact of Cross-Domain Data on German Language Models

Kavli Affiliate: Cheng Peng | First 5 Authors: Amin Dada, Aokun Chen, Cheng Peng, Kaleb E Smith, Ahmad Idrissi-Yaghir | Summary: Traditionally, large language models have been either trained on general web crawls or domain-specific data. However, recent successes of generative large language models, have shed light on the benefits of cross-domain datasets. To examine […]


Continue.. On the Impact of Cross-Domain Data on German Language Models

Lyman Continuum Emission from Spectroscopically Confirmed Ly$α$ Emitters at $zsim3.1$

Kavli Affiliate: Linhua Jiang | First 5 Authors: , , , , | Summary: We present a study of Lyman continuum (LyC) emission in a sample of $sim$150 Ly$alpha$ emitters (LAEs) at $zapprox3.1$ in the Subaru-XMM Deep Survey field. These LAEs were previously selected using the narrowband technique and spectroscopically confirmed with Ly$alpha$ equivalent widths […]


Continue.. Lyman Continuum Emission from Spectroscopically Confirmed Ly$α$ Emitters at $zsim3.1$

The Slicer Combined with Array of Lenslets for Exoplanet Spectroscopy (SCALES): driving science cases and expected outcomes

Kavli Affiliate: Bruce Macintosh | First 5 Authors: , , , , | Summary: The Slicer Combined with Array of Lenslets for Exoplanet Spectroscopy (SCALES) is a $2-5~mu$m, high-contrast integral field spectrograph (IFS) currently being built for Keck Observatory. With both low ($Rlesssim250$) and medium ($Rsim3500-7000$) spectral resolution IFS modes, SCALES will detect and characterize […]


Continue.. The Slicer Combined with Array of Lenslets for Exoplanet Spectroscopy (SCALES): driving science cases and expected outcomes

The classical field approximation of ultra light dark matter: quantum breaktimes, corrections, and decoherence

Kavli Affiliate: Tom Abel | First 5 Authors: Andrew Eberhardt, Alvaro Zamora, Michael Kopp, Tom Abel, | Summary: The classical field approximation is widely used to better understand the predictions of ultra-light dark matter. Here, we use the truncated Wigner approximation method to test the classical field approximation of ultra-light dark matter. This method approximates […]


Continue.. The classical field approximation of ultra light dark matter: quantum breaktimes, corrections, and decoherence

The Temporal Structure of Language Processing in the Human Brain Corresponds to The Layered Hierarchy of Deep Language Models

Kavli Affiliate: Michael Brenner | First 5 Authors: Ariel Goldstein, Eric Ham, Mariano Schain, Samuel Nastase, Zaid Zada | Summary: Deep Language Models (DLMs) provide a novel computational paradigm for understanding the mechanisms of natural language processing in the human brain. Unlike traditional psycholinguistic models, DLMs use layered sequences of continuous numerical vectors to represent […]


Continue.. The Temporal Structure of Language Processing in the Human Brain Corresponds to The Layered Hierarchy of Deep Language Models

Mapping energy landscapes of homopolymeric RNAs via simulated tempering and deep unsupervised learning

Kavli Affiliate: V. S. Ramachandran | Authors: Vysakh Ramachandran and Davit A Potoyan | Summary: Conformational dynamics plays crucial roles in RNA functions about sensing and responding to environmental signals. The liquid-liquid phase separation of RNAs and the formation of stress granules partly relies on RNA’s conformational plasticity and its ability to engage in multivalent […]


Continue.. Mapping energy landscapes of homopolymeric RNAs via simulated tempering and deep unsupervised learning