Kavli Affiliate: Andrey Kravtsov | First 5 Authors: Yue Pan, Andrey Kravtsov, , , | Summary: We investigate the impact of bursty star formation on several galaxy scaling relations of dwarf galaxies using the $texttt{GRUMPY}$ galaxy formation model. While this model reproduces the star formation rate (SFR)-stellar mass, stellar mass-gas mass, and stellar mass-metallicity relations, […]
Kavli Affiliate: Stephan S. Meyer | First 5 Authors: Rebecca Diesing, Stephan S. Meyer, Johannes Eser, Alexa Bukowski, Alex Miller | Summary: The second generation of the Extreme Universe Space Observatory on a Super Pressure Balloon (EUSO-SPB2) is a balloon instrument that searched for ultra high energy cosmic rays (UHECRs) with energies above 1 EeV […]
Kavli Affiliate: Chihway Chang | First 5 Authors: Dhayaa Anbajagane, Chihway Chang, Hayden Lee, Marco Gatti, | Summary: Primordial non-Gaussianities (PNGs) are signatures in the density field that encode particle physics processes from the inflationary epoch. Such signatures have been extensively studied using the Cosmic Microwave Background, through constraining the amplitudes, $f^{X}_{rm NL}$, with future […]
Kavli Affiliate: Wei Gao | First 5 Authors: Xuan Zhang, Wei Gao, , , | Summary: While large pre-trained language models (LLMs) have shown their impressive capabilities in various NLP tasks, they are still under-explored in the misinformation domain. In this paper, we examine LLMs with in-context learning (ICL) for news claim verification, and find […]
Kavli Affiliate: Brett Fors | First 5 Authors: Steven J. Yang, Stephanie I. Rosenbloom, Brett P. Fors, Meredith N. Silberstein, | Summary: Phase-segregated polyureas (PU) have received considerable interest due to their use as tough, impact-resistant coatings. Polyureas are favored for these applications due to their mechanical strain rate sensitivity and energy dissipation. Predicting and […]
Kavli Affiliate: Wei Gao | First 5 Authors: Haoming Wang, Wei Gao, , , | Summary: The efficiency of Federated Learning (FL) is often affected by both data and device heterogeneities. Data heterogeneity is defined as the heterogeneity of data distributions on different clients. Device heterogeneity is defined as the clients’ variant latencies in uploading […]
Kavli Affiliate: Wei Gao | First 5 Authors: Haoming Wang, Wei Gao, , , | Summary: The efficiency of Federated Learning (FL) is often affected by both data and device heterogeneities. Data heterogeneity is defined as the heterogeneity of data distributions on different clients. Device heterogeneity is defined as the clients’ variant latencies in uploading […]
Kavli Affiliate: Wei Gao | First 5 Authors: Haoming Wang, Wei Gao, , , | Summary: Federated Learning (FL) can be affected by data and device heterogeneities, caused by clients’ different local data distributions and latencies in uploading model updates (i.e., staleness). Traditional schemes consider these heterogeneities as two separate and independent aspects, but this […]
Kavli Affiliate: Wei Gao | First 5 Authors: Haoming Wang, Wei Gao, , , | Summary: Federated Learning (FL) can be affected by data and device heterogeneities, caused by clients’ different local data distributions and latencies in uploading model updates (i.e., staleness). Traditional schemes consider these heterogeneities as two separate and independent aspects, but this […]
Kavli Affiliate: Wei Gao | First 5 Authors: Kai Huang, Hanyun Yin, Heng Huang, Wei Gao, | Summary: Fine-tuning is the most effective way of adapting pre-trained large language models (LLMs) to downstream applications. With the fast growth of LLM-enabled AI applications and democratization of open-souced LLMs, fine-tuning has become possible for non-expert individuals, but […]