Document Level Machine Translation

12 papers with code • 1 benchmarks • 1 datasets

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Most implemented papers

BlonDe: An Automatic Evaluation Metric for Document-level Machine Translation

eleanorjiang/blonde NAACL 2022

Standard automatic metrics, e. g. BLEU, are not reliable for document-level MT evaluation.

Using Coreference Links to Improve Spanish-to-English Machine Translation

idiap/APT WS 2017

In this paper, we present a proof-of-concept implementation of a coreference-aware decoder for document-level machine translation.

A Survey on Document-level Neural Machine Translation: Methods and Evaluation

SFFAI-AIKT/AIKT-Natural_Language_Processing 18 Dec 2019

Machine translation (MT) is an important task in natural language processing (NLP) as it automates the translation process and reduces the reliance on human translators.

Towards Making the Most of Context in Neural Machine Translation

blickwinkel1107/making-the-most-of-context-nmt 19 Feb 2020

Document-level machine translation manages to outperform sentence level models by a small margin, but have failed to be widely adopted.

Measuring and Increasing Context Usage in Context-Aware Machine Translation

neulab/contextual-mt ACL 2021

Recent work in neural machine translation has demonstrated both the necessity and feasibility of using inter-sentential context -- context from sentences other than those currently being translated.

G-Transformer for Document-level Machine Translation

baoguangsheng/g-transformer ACL 2021

However, study shows that when we further enlarge the translation unit to a whole document, supervised training of Transformer can fail.

DiscoScore: Evaluating Text Generation with BERT and Discourse Coherence

aiphes/discoscore 26 Jan 2022

Still, recent BERT-based evaluation metrics are weak in recognizing coherence, and thus are not reliable in a way to spot the discourse-level improvements of those text generation systems.

Modeling Context With Linear Attention for Scalable Document-Level Translation

zhaofengwu/rfa-doc-mt 16 Oct 2022

Document-level machine translation leverages inter-sentence dependencies to produce more coherent and consistent translations.

Document-Level Machine Translation with Large Language Models

longyuewangdcu/document-mt-llm 5 Apr 2023

Large language models (LLMs) such as Chat-GPT can produce coherent, cohesive, relevant, and fluent answers for various natural language processing (NLP) tasks.

Target-Side Augmentation for Document-Level Machine Translation

baoguangsheng/target-side-augmentation 8 May 2023

Document-level machine translation faces the challenge of data sparsity due to its long input length and a small amount of training data, increasing the risk of learning spurious patterns.