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Found 14 papers, 3 papers with code
CSP:Code-Switching Pre-training for Neural Machine Translation
Unlike traditional pre-training method which randomly masks some fragments of the input sentence, the proposed CSP randomly replaces some words in the source sentence with their translation words in the target language.
TenTrans Large-Scale Multilingual Machine Translation System for WMT21
This paper describes TenTrans large-scale multilingual machine translation system for WMT 2021.
TenTrans Multilingual Low-Resource Translation System for WMT21 Indo-European Languages Task
This paper describes TenTrans’ submission to WMT21 Multilingual Low-Resource Translation shared task for the Romance language pairs.
TenTrans High-Performance Inference Toolkit for WMT2021 Efficiency Task
The paper describes the TenTrans’s submissions to the WMT 2021 Efficiency Shared Task.
Speeding up Transformer Decoding via an Attention Refinement Network
Extensive experiments on ten WMT machine translation tasks show that the proposed model yields an average of 1. 35x faster (with almost no decrease in BLEU) over the state-of-the-art inference implementation.
AlignDistil: Token-Level Language Model Alignment as Adaptive Policy Distillation
However, in most existing methods for LLM alignment, all tokens in the response are optimized using a sparse, response-level reward or preference annotation.
Continual Learning of Neural Machine Translation within Low Forgetting Risk Regions
Specifically, we propose two methods to search the low forgetting risk regions, which are based on the curvature of loss and the impacts of the parameters on the model output, respectively.
Increasing Visual Awareness in Multimodal Neural Machine Translation from an Information Theoretic Perspective
Multimodal machine translation (MMT) aims to improve translation quality by equipping the source sentence with its corresponding image.
Stacked Acoustic-and-Textual Encoding: Integrating the Pre-trained Models into Speech Translation Encoders
To our knowledge, we are the first to develop an end-to-end ST system that achieves comparable or even better BLEU performance than the cascaded ST counterpart when large-scale ASR and MT data is available.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
Dynamic Curriculum Learning for Low-Resource Neural Machine Translation
This eases training by highlighting easy samples that the current model has enough competence to learn.
Low Resource Neural Machine Translation
Low-Resource Neural Machine Translation
+3
Code-switching pre-training for neural machine translation
Unlike traditional pre-training method which randomly masks some fragments of the input sentence, the proposed CSP randomly replaces some words in the source sentence with their translation words in the target language.
Learn to Segment Retinal Lesions and Beyond
This paper attacks the three challenges in the context of diabetic retinopathy (DR) grading.
TencentFmRD Neural Machine Translation for WMT18
Our systems are neural machine translation systems trained with our original system TenTrans.
