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Data Proportion Detection for Optimized Data Management for Large Language Models

Autor: Liang, Hao, Zhao, Keshi, Yang, Yajie, Cui, Bin, Dong, Guosheng, Zhou, Zenan, Zhang, Wentao

Large language models (LLMs) have demonstrated exceptional performance across a wide range of tasks and domains, with data preparation playing a critical role in achieving these results. Pre-training data typically combines information from multiple

Externí odkaz: http://arxiv.org/abs/2409.17527

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Akademický článek

MXenes for future nanophotonic device applications

Autor: Jeon Jaeho, Yang Yajie, Choi Haeju, Park Jin-Hong, Lee Byoung Hun, Lee Sungjoo

Publikováno v: Nanophotonics, Vol 9, Iss 7, Pp 1831-1853 (2020)

Two-dimensional (2D) layers of transition metal carbides, nitrides, or carbonitrides, collectively referred to as MXenes, are considered as the new family of 2D materials for the development of functional building blocks for optoelectronic and photon

Externí odkaz: https://doaj.org/article/9778d5052b1d43e893c382cea6fe8997

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Channel-Spatial-Based Few-Shot Bird Sound Event Detection

Autor: Liu, Lingwen, Feng, Yuxuan, Fu, Haitao, Yang, Yajie, Pan, Xin, Jin, Chenlei

In this paper, we propose a model for bird sound event detection that focuses on a small number of training samples within the everyday long-tail distribution. As a result, we investigate bird sound detection using the few-shot learning paradigm. By

Externí odkaz: http://arxiv.org/abs/2306.10499

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