Zobrazeno 1 - 10
of 701
pro vyhledávání: '"Cui Xiaodong"'
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
The integration of external personalized context information into document-grounded conversational systems has significant potential business value, but has not been well-studied. Motivated by the concept of personalized context-aware document-ground
Externí odkaz:
http://arxiv.org/abs/2308.13760
We improve on the popular conformer architecture by replacing the depthwise temporal convolutions with diagonal state space (DSS) models. DSS is a recently introduced variant of linear RNNs obtained by discretizing a linear dynamical system with a di
Externí odkaz:
http://arxiv.org/abs/2302.14120
We first propose a decentralized proximal stochastic gradient tracking method (DProxSGT) for nonconvex stochastic composite problems, with data heterogeneously distributed on multiple workers in a decentralized connected network. To save communicatio
Externí odkaz:
http://arxiv.org/abs/2302.14252