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Found 18 papers, 1 papers with code
Overcoming Vocabulary Constraints with Pixel-level Fallback
Subword tokenization requires balancing computational efficiency and vocabulary coverage, which often leads to suboptimal performance on languages and scripts not prioritized during training.
Learning Language-Specific Layers for Multilingual Machine Translation
Multilingual Machine Translation promises to improve translation quality between non-English languages.
State Spaces Aren't Enough: Machine Translation Needs Attention
Structured State Spaces for Sequences (S4) is a recently proposed sequence model with successful applications in various tasks, e. g. vision, language modeling, and audio.
Non-Autoregressive Neural Machine Translation: A Call for Clarity
Non-autoregressive approaches aim to improve the inference speed of translation models by only requiring a single forward pass to generate the output sequence instead of iteratively producing each predicted token.
Jointly Learning to Align and Translate with Transformer Models
The state of the art in machine translation (MT) is governed by neural approaches, which typically provide superior translation accuracy over statistical approaches.
Local System Voting Feature for Machine Translation System Combination
In this paper, we enhance the traditional confusion network system combination approach with an additional model trained by a neural network.
