![]() The accuracy of NAT models is therefore improved significantly over the state-of-the-art NAT models with even better efficiency for inference. ago why would the rules to make the olympics make a difference for him He qualified for the olympics big time, the Chinese team just didn’t pick him as one of the 4 men to go (presumably) because of his low made lift percentage compared to other lifters. 58 Yu Sun, Qian Bao, Wu Liu, Yili Fu, Michael J Black, and Tao. Extensive experiments conducted on several benchmark datasets show that both regularization strategies are effective and can alleviate the issues of repeated translations and incomplete translations in NAT models. paper, we address human mesh recovery in multi-person. ![]() In 1991, Tao founded Top Capital, the first Chinese magazine on private equity investment, and has served as its editor-inchief since then. Second, to force the hidden states to contain all the information in the source sentence, we leverage the dual nature of translation tasks (e.g., English to German and German to English) and minimize a backward reconstruction error to ensure that the hidden states of the NAT decoder are able to recover the source side sentence. Tian Tao is a member of the Huawei International Advisory Council and codirector of Ruihua Innovative Research Institute at Zhejiang University, Hangzhou, China. First, to make the hidden states more distinguishable, we regularize the similarity between consecutive hidden states based on the corresponding target tokens. Not only that, but Tao did not move his torso muscles. That’s more than three times Tao’s weight It is unclear if Tao is working to move up from the 85kg to the 89kg weight category, but the lift is amazing nonetheless. ![]() In this paper, we propose to address these two problems by improving the quality of decoder hidden representations via two auxiliary regularization terms in the training process of an NAT model. Intro CHERNOBYL AZ-5 why it exploded Mike Bell 29.7K subscribers Subscribe 3. Shenzhen Weightlifting promoted an Instagram video this week of Tian Tao completing a front squat of 280kg or 617lb. There’s no hype music, no cheering, and only a faint glimmer of a smile as the athlete unracks. However, the high efficiency has come at the cost of not capturing the sequential dependency on the target side of translation, which causes NAT to suffer from two kinds of translation errors: 1) repeated translations (due to indistinguishable adjacent decoder hidden states), and 2) incomplete translations (due to incomplete transfer of source side information via the decoder hidden states). Very, very strong Chinese weightlifter Tian Tao just made a 310 kilogram squat look like a warmup. University of Illinois at Urbana-ChampaignĪs a new neural machine translation approach, NonAutoregressive machine Translation (NAT) has attracted attention recently due to its high efficiency in inference.
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