Neural Machine Translation (NMT) generates target words sequentially in the way of predicting the next word conditioned on the context words. At training time, it predicts with the ground truth words as context while at inference it has to generate the entire sequence from scratch. This discrepancy of the fed context leads to error accumulation among the way. Furthermore, word-level training requires strict matching between the generated sequence and the ground truth sequence which leads to overcorrection over different but reasonable translations. In this paper, we address these issues by sampling context words not only from the ground truth sequence but also from the predicted sequence by the model during training, where the predicted sequence is selected with a sentence-level optimum. Experiment results on Chinese→English and WMT'14 English→German translation tasks demonstrate that our approach can achieve significant improvements on multiple datasets.

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We conducted this meta-analysis to explore the prognostic value of outpatient (or office) hysteroscopy (OH) preceding in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI) cycles in women who had experienced repeated implantation failure (RIF), particularly in regard to the conflicting evidence reported by previous studies. Two reviewers independently searched Pubmed, MEDLINE, Web of Science, Cochrane Library and Embase to identify all publications of clinical trials of hysteroscopy with or without endometrial biopsy in RIF patients. The primary outcome measures were clinical pregnancy rate (CPR) and live birth rate (LBR). Pooled relative ratios (RRs) with 95% confidence intervals (CIs) were calculated. Publication bias was detected using funnel plots and Egger's regression tests. Six eligible studies comprising 4143 patients were included. The CPR and LBR were both significantly higher in RIF patients with OH than RIF patients without OH (CPR: RR 1.34, 95% CI 1.14-1.57, P < 0.05; LBR: RR 1.29, 95% CI 1.03-1.62, P < 0.05). Subgroup analysis revealed a significant association between OH and CPR in Asia (CPR: RR 1.49, 95% CI 1.31-1.69; P < 0.05) rather than in Europe (CPR: RR 1.08, 95% CI 0.93-1.26; P = 0.291). However, there was no evidence of a significant difference in either CPR or LBR between the normal and abnormal OH groups (CPR: RR 0.92, 95% CI 0.83-1.02, P = 0.12; LBR: RR 0.76, 95% CI 0.37-1.56, P = 0.450). Hysteroscopy may potentially improve pregnancy outcomes in patients with RIP.

This paper reviews the NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video. In this challenge, we proposed the LDV 2.0 dataset, which includes the LDV dataset (240 videos) and 95 additional videos. This challenge includes three tracks. Track 1 aims at enhancing the videos compressed by HEVC at a fixed QP. Track 2 and Track 3 target both the superresolution and quality enhancement of HEVC compressed video. They require x2 and x4 super-resolution, respectively. The three tracks totally attract more than 600 registrations. In the test phase, 8 teams, 8 teams and 12 teams submitted the final results to Tracks 1, 2 and 3, respectively. The proposed methods and solutions gauge the state-of-the-art of super-resolution and quality enhancement of compressed video. The proposed LDV 2.0 dataset is available at https://github.com/RenYanghome/LDV_dataset. The homepage of this challenge (including open-sourced codes) is at https://github. com/RenYang-home/NTIRE22_VEnh_SR.