Modulation Instability and Wavenumber Bandgap Breathers in a Time Layered Phononic Lattice

Kavli Affiliate: Chiara Daraio | First 5 Authors: Christopher Chong, Brian Kim, Evelyn Wallace, Chiara Daraio, | Summary: We demonstrate the existence of wavenumber bandgap (q-gap) breathers in a time-periodic phononic lattice. These breathers are localized in time and periodic in space, and are the counterparts to the classical breathers found in spatially-periodic systems. We […]


Continue.. Modulation Instability and Wavenumber Bandgap Breathers in a Time Layered Phononic Lattice

Multi-Modal Knowledge Graph Transformer Framework for Multi-Modal Entity Alignment

Kavli Affiliate: Lihong Wang | First 5 Authors: Qian Li, Cheng Ji, Shu Guo, Zhaoji Liang, Lihong Wang | Summary: Multi-Modal Entity Alignment (MMEA) is a critical task that aims to identify equivalent entity pairs across multi-modal knowledge graphs (MMKGs). However, this task faces challenges due to the presence of different types of information, including […]


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Phonon engineering of atomic-scale defects in superconducting quantum circuits

Kavli Affiliate: Oskar Painter | First 5 Authors: Mo Chen, John Clai Owens, Harald Putterman, Max Schäfer, Oskar Painter | Summary: Noise within solid-state systems at low temperatures, where many of the degrees of freedom of the host material are frozen out, can typically be traced back to material defects that support low-energy excitations. These […]


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Hot electron diffusion, microwave noise, and piezoresistivity in Si from first principles

Kavli Affiliate: Austin J. Minnich | First 5 Authors: Benjamin Hatanpää, Austin J. Minnich, , , | Summary: Ab-initio calculations of charge transport properties in materials without adjustable parameters have provided microscopic insights into electron-phonon interactions which govern charge transport properties. Other transport properties such as the diffusion coefficient provide additional microscopic information and are […]


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Towards LLM-based Fact Verification on News Claims with a Hierarchical Step-by-Step Prompting Method

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 […]


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Noise Reduction Methods for Large-scale Intensity-mapping Measurements with Infrared Detector Arrays

Kavli Affiliate: James Bock | First 5 Authors: Grigory Heaton, Walter Cook, James Bock, Jill Burnham, Sam Condon | Summary: Intensity mapping observations measure galaxy clustering fluctuations from spectral-spatial maps, requiring stable noise properties on large angular scales. We have developed specialized readouts and analysis methods for achieving large-scale noise stability with Teledyne 2048$times$2048 H2RG […]


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Tackling the Unlimited Staleness in Federated Learning with Intertwined Data and Device Heterogeneities

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 […]


Continue.. Tackling the Unlimited Staleness in Federated Learning with Intertwined Data and Device Heterogeneities

Tackling the Unlimited Staleness in Federated Learning with Intertwined Data and Device Heterogeneities

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 […]


Continue.. Tackling the Unlimited Staleness in Federated Learning with Intertwined Data and Device Heterogeneities

Tackling the Unlimited Staleness in Federated Learning with Intertwined Data and Device Heterogeneities

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 […]


Continue.. Tackling the Unlimited Staleness in Federated Learning with Intertwined Data and Device Heterogeneities

Tackling Intertwined Data and Device Heterogeneities in Federated Learning with Unlimited Staleness

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 […]


Continue.. Tackling Intertwined Data and Device Heterogeneities in Federated Learning with Unlimited Staleness