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Showing 51–82 of 82 papers

TitleStatusHype
Normalization of Input-output Shared Embeddings in Text Generation Models—0
The University of Edinburgh-Uppsala University’s Submission to the WMT 2020 Chat Translation Task—0
On Synthetic Data for Back Translation—0
Tuning Large language model for End-to-end Speech Translation—0
On the Importance of Local Information in Transformer Based Models—0
On the Sub-Layer Functionalities of Transformer Decoder—0
On Using Monolingual Corpora in Neural Machine Translation—0
Predictive Attention Transformer: Improving Transformer with Attention Map Prediction—0
Proactive Sequence Generator via Knowledge Acquisition—0
Prompting LLMs: Length Control for Isometric Machine Translation—0
An Enhanced Text Compression Approach Using Transformer-based Language Models—0
Character-level Transformer-based Neural Machine Translation—0
VETRA: A Dataset for Vehicle Tracking in Aerial Imagery - New Challenges for Multi-Object Tracking—0
Self-Adaptive Scaling for Learnable Residual Structure—0
SelfSeg: A Self-supervised Sub-word Segmentation Method for Neural Machine Translation—0
Attention Link: An Efficient Attention-Based Low Resource Machine Translation Architecture—0
Vocabulary Adaptation for Distant Domain Adaptation in Neural Machine Translation—0
AR: Auto-Repair the Synthetic Data for Neural Machine Translation—0
Structured in Space, Randomized in Time: Leveraging Dropout in RNNs for Efficient Training—0
Task-Level Curriculum Learning for Non-Autoregressive Neural Machine Translation—0
Addressing Posterior Collapse with Mutual Information for Improved Variational Neural Machine Translation—0
Findings of the WMT 2019 Biomedical Translation Shared Task: Evaluation for MEDLINE Abstracts and Biomedical Terminologies—0
Exploring Adequacy Errors in Neural Machine Translation with the Help of Cross-Language Aligned Word Embeddings—0
The HW-TSC’s Offline Speech Translation System for IWSLT 2022 Evaluation—0
Embedding-Enhanced GIZA++: Improving Low-Resource Word Alignment Using Embeddings—0
Glossary functionality in commercial machine translation: does it help? A first step to identify best practices for a language service provider—0
Hint-based Training for Non-Autoregressive Translation—0
The RWTH Aachen University Machine Translation Systems for WMT 2019—0
HW-TSC’s Participation in the WMT 2021 News Translation Shared Task—0
The Samsung and University of Edinburgh’s submission to IWSLT17—0
Improving Autoregressive NMT with Non-Autoregressive Model—0
Improving End-to-end Speech Translation by Leveraging Auxiliary Speech and Text Data—0
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