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1
Universal Conditional Masked Language Pre-training for Neural Machine Translation ...
Li, Pengfei; Li, Liangyou; Zhang, Meng. - : arXiv, 2022
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2
Compilable Neural Code Generation with Compiler Feedback ...
Wang, Xin; Wang, Yasheng; Wan, Yao. - : arXiv, 2022
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3
Sub-Character Tokenization for Chinese Pretrained Language Models ...
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4
Training Multilingual Pre-trained Language Model with Byte-level Subwords ...
Wei, Junqiu; Liu, Qun; Guo, Yinpeng. - : arXiv, 2021
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5
Multilingual Speech Translation with Unified Transformer: Huawei Noah's Ark Lab at IWSLT 2021 ...
Zeng, Xingshan; Li, Liangyou; Liu, Qun. - : arXiv, 2021
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6
JABER and SABER: Junior and Senior Arabic BERt ...
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7
Learning Multilingual Representation for Natural Language Understanding with Enhanced Cross-Lingual Supervision ...
Guo, Yinpeng; Li, Liangyou; Jiang, Xin. - : arXiv, 2021
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8
LightMBERT: A Simple Yet Effective Method for Multilingual BERT Distillation ...
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9
Uncertainty-Aware Balancing for Multilingual and Multi-Domain Neural Machine Translation Training ...
Wu, Minghao; Li, Yitong; Zhang, Meng. - : arXiv, 2021
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10
Improving Unsupervised Question Answering via Summarization-Informed Question Generation ...
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11
CCA-MDD: A Coupled Cross-Attention based Framework for Streaming Mispronunciation detection and diagnosis ...
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12
A Mutual Information Maximization Approach for the Spurious Solution Problem in Weakly Supervised Question Answering ...
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13
HyKnow: End-to-End Task-Oriented Dialog Modeling with Hybrid Knowledge Management ...
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14
AutoTinyBERT: Automatic Hyper-parameter Optimization for Efficient Pre-trained Language Models ...
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15
TGEA: An Error-Annotated Dataset and Benchmark Tasks for TextGeneration from Pretrained Language Models ...
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16
Two Parents, One Child: {D}ual Transfer for Low-Resource Neural Machine Translation ...
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17
RealTranS: End-to-End Simultaneous Speech Translation with Convolutional Weighted-Shrinking Transformer ...
Abstract: Read paper: https://www.aclanthology.org/2021.findings-acl.218 Abstract: End-to-end simultaneous speech translation (SST), which directly translates speech in one language into text in another language in real-time, is useful in many scenarios but has not been fully investigated. In this work, we propose RealTranS, an end-to-end model for SST. To bridge the modality gap between speech and text, RealTranS gradually downsamples the input speech with interleaved convolution and unidirectional Transformer layers for acoustic modeling, and then maps speech features into text space with a weighted-shrinking operation and a semantic encoder. Besides, to improve the model performance in simultaneous scenarios, we propose a blank penalty to enhance the shrinking quality and a Wait-K-Stride-N strategy to allow local reranking during decoding. Experiments on public and widely-used datasets show that RealTranS with the Wait-K-Stride-N strategy outperforms prior end-to-end models as well as cascaded models in diverse ...
Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics
URL: https://underline.io/lecture/26309-realtrans-end-to-end-simultaneous-speech-translation-with-convolutional-weighted-shrinking-transformer
https://dx.doi.org/10.48448/3s3m-5861
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18
Uncertainty-Aware Balancing for Multilingual and Multi-Domain Neural Machine Translation Training ...
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19
DyLex: Incorporating Dynamic Lexicons into BERT for Sequence Labeling ...
Wang, Baojun; Zhang, Zhao; Xu, Kun. - : arXiv, 2021
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20
Document Graph for Neural Machine Translation ...
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