Zobrazeno 1 - 10
of 750
pro vyhledávání: '"Cui, XiaoDong"'
Autor:
Cui, Xiaodong, Saif, A F M, Lu, Songtao, Chen, Lisha, Chen, Tianyi, Kingsbury, Brian, Saon, George
In this paper, we propose a bilevel joint unsupervised and supervised training (BL-JUST) framework for automatic speech recognition. Compared to the conventional pre-training and fine-tuning strategy which is a disconnected two-stage process, BL-JUST
Externí odkaz:
http://arxiv.org/abs/2412.08548
Autor:
Kai, Feng, Wang, Xiong, Xie, Yiqin, Yang, Yuhui, Watanabe, Kenji, Taniguchi, Takashi, Yu, Hongyi, Yao, Wang, Cui, Xiaodong
This letter reports a time resolved pump-probe reflectance spectroscopic study on moir\'e excitons in a twisted monolayer WS2/WSe2 heterostructure. By probing at the resonant energies of intralayer excitons, we observed their distinct temporal tracks
Externí odkaz:
http://arxiv.org/abs/2410.04893
Chain-of-Thought (CoT) is an efficient prompting method that enables the reasoning ability of large language models by augmenting the query using multiple examples with multiple intermediate steps. Despite the empirical success, the theoretical under
Externí odkaz:
http://arxiv.org/abs/2410.02167
Graph Neural Network (GNN) has achieved remarkable success in various graph learning tasks, such as node classification, link prediction and graph classification. The key to the success of GNN lies in its effective structure information representatio
Externí odkaz:
http://arxiv.org/abs/2405.18824
Autor:
Liu, Qiye, Su, Wenjie, Gu, Yue, Zhang, Xi, Xia, Xiuquan, Wang, Le, Xiao, Ke, Cui, Xiaodong, Zou, Xiaolong, Xi, Bin, Mei, Jia-Wei, Dai, Jun-Feng
Interlayer magnetic interactions play a pivotal role in determining the magnetic arrangement within van der Waals (vdW) magnets, and the remarkable tunability of these interactions through applied pressure further enhances their significance. Here, w
Externí odkaz:
http://arxiv.org/abs/2404.09569
Transformer-based large language models have displayed impressive in-context learning capabilities, where a pre-trained model can handle new tasks without fine-tuning by simply augmenting the query with some input-output examples from that task. Desp
Externí odkaz:
http://arxiv.org/abs/2402.15607
Joint Unsupervised and Supervised Training for Automatic Speech Recognition via Bilevel Optimization
In this paper, we present a novel bilevel optimization-based training approach to training acoustic models for automatic speech recognition (ASR) tasks that we term {bi-level joint unsupervised and supervised training (BL-JUST)}. {BL-JUST employs a l
Externí odkaz:
http://arxiv.org/abs/2401.06980
Soft random sampling (SRS) is a simple yet effective approach for efficient training of large-scale deep neural networks when dealing with massive data. SRS selects a subset uniformly at random with replacement from the full data set in each epoch. I
Externí odkaz:
http://arxiv.org/abs/2311.12727
With the shrinking of dimensionality, Coulomb interactions play a distinct role in two-dimensional (2D) semiconductors owing to the reduced dielectric screening in the out-of-plane direction. Apart from dielectric screening, free charge carriers and/
Externí odkaz:
http://arxiv.org/abs/2309.14101
Autor:
Xiao, Ke, Yan, Tengfei, Xiao, Chengxin, Fan, Feng-ren, Duan, Ruihuan, Liu, Zheng, Watanabe, Kenji, Taniguchi, Takashi, Yao, Wang, Cui, Xiaodong
The potential for low-threshold optical nonlinearity has received significant attention in the fields of photonics and conceptual optical neuron networks. Excitons in two-dimensional (2D) semiconductors are particularly promising in this regard as re
Externí odkaz:
http://arxiv.org/abs/2308.14362