Papers Document Level Machine Translation
“Document Level Machine Translation” 태그가 달린 논문 58편 · 필터 해제
Revamping Multilingual Agreement Bidirectionally via Switched Back-translation for Multilingual Neural Machine Translation
Despite the fact that multilingual agreement (MA) has shown its importance for multilingual neural machine translation (MNMT), current methodologies in the field have two shortages: (i) require parallel data between mult…
Document Level Machine TranslationDocument TranslationMachine TranslationTranslationDELA Project: Document-level Machine Translation Evaluation
This paper presents the results of the DELA Project. We describe the testing of context span for document-level evaluation, construction of a document-level corpus, and context position, as well as the latest development…
Document Level Machine TranslationMachine TranslationPositionTranslationTANDO: A Corpus for Document-level Machine Translation
Document-level Neural Machine Translation aims to increase the quality of neural translation models by taking into account contextual information. Properly modelling information beyond the sentence level can result in im…
Document Level Machine TranslationMachine TranslationSentenceTranslationLearn To Remember: Transformer with Recurrent Memory for Document-Level Machine Translation
The Transformer architecture has led to significant gains in machine translation. However, most studies focus on only sentence-level translation without considering the context dependency within documents, leading to the…
Document Level Machine TranslationMachine TranslationSentenceTranslationLocality-Sensitive Hashing for Long Context Neural Machine Translation
After its introduction the Transformer architecture quickly became the gold standard for the task of neural machine translation. A major advantage of the Transformer compared to previous architectures is the faster train…
Document Level Machine TranslationMachine TranslationNMTSentence+1DiscoScore: Evaluating Text Generation with BERT and Discourse Coherence
Recently, there has been a growing interest in designing text generation systems from a discourse coherence perspective, e.g., modeling the interdependence between sentences. Still, recent BERT-based evaluation metrics a…
Document Level Machine TranslationMachine TranslationText Generation{BlonDe}: An Automatic Evaluation Metric for Document-level Machine Translation
Standard automatic metrics, e.g. BLEU, are not reliable for document-level MT evaluation. They can neither distinguish document-level improvements in translation quality from sentence-level ones, nor identify the discour…
Document Level Machine TranslationMachine TranslationSentenceTranslationDocument-level Neural Machine Translation Using Dependency RST Structure
Document-level machine translation (MT) extends the translation unit from the sentence to the whole document. Intuitively, discourse structure can be useful for document-level MT for its helpfulness in long-range depende…
DecoderDocument Level Machine TranslationMachine TranslationNMT+2SMDT: Selective Memory-Augmented Neural Document Translation
Existing document-level neural machine translation (NMT) models have sufficiently explored different context settings to provide guidance for target generation. However, little attention is paid to inaugurate more divers…
Document Level Machine TranslationDocument TranslationMachine TranslationNMT+2Document Level Hierarchical Transformer
Generating long and coherent text is an important and challenging task encompassing many application areas such as summarization, document level machine translation and story generation. Despite the success in modeling i…
Document Level Machine TranslationImitation LearningMachine TranslationSentence+2Contrastive Learning for Context-aware Neural Machine Translation Using Coreference Information
Context-aware neural machine translation (NMT) incorporates contextual information of surrounding texts, that can improve the translation quality of document-level machine translation. Many existing works on context-awar…
Contrastive Learningcoreference-resolutionCoreference ResolutionData Augmentation+5Contrastive Learning for Context-aware Neural Machine TranslationUsing Coreference Information
Context-aware neural machine translation (NMT) incorporates contextual information of surrounding texts, that can improve the translation quality of document-level machine translation. Many existing works on context-awar…
Contrastive Learningcoreference-resolutionCoreference ResolutionData Augmentation+5Multi-Hop Transformer for Document-Level Machine Translation
Document-level neural machine translation (NMT) has proven to be of profound value for its effectiveness on capturing contextual information. Nevertheless, existing approaches 1) simply introduce the representations of c…
Document Level Machine TranslationDocument TranslationMachine TranslationNMT+2G-Transformer for Document-level Machine Translation
Document-level MT models are still far from satisfactory. Existing work extend translation unit from single sentence to multiple sentences. However, study shows that when we further enlarge the translation unit to a whol…
Document Level Machine TranslationInductive BiasMachine TranslationSentence+1Measuring and Increasing Context Usage in Context-Aware Machine Translation
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. However, while many c…
Document Level Machine TranslationMachine TranslationTranslationHierarchical Learning for Generation with Long Source Sequences
One of the challenges for current sequence to sequence (seq2seq) models is processing long sequences, such as those in summarization and document level machine translation tasks. These tasks require the model to reason a…
DecoderDocument Level Machine TranslationDocument SummarizationDocument Translation+6Towards Personalised and Document-level Machine Translation of Dialogue
State-of-the-art (SOTA) neural machine translation (NMT) systems translate texts at sentence level, ignoring context: intra-textual information, like the previous sentence, and extra-textual information, like the gender …
Document Level Machine TranslationMachine TranslationNMTSentence+1BlonDe: An Automatic Evaluation Metric for Document-level Machine Translation
Standard automatic metrics, e.g. BLEU, are not reliable for document-level MT evaluation. They can neither distinguish document-level improvements in translation quality from sentence-level ones, nor identify the discour…
Document Level Machine TranslationMachine TranslationSentenceTranslationTowards Personalised and Document-level Machine Translation of Dialogue
State-of-the-art (SOTA) neural machine translation (NMT) systems translate texts at sentence level, ignoring context: intra-textual information, like the previous sentence, and extra-textual information, like the gender …
Document Level Machine TranslationMachine TranslationNMTSentence+1A Comparison of Approaches to Document-level Machine Translation
Document-level machine translation conditions on surrounding sentences to produce coherent translations. There has been much recent work in this area with the introduction of custom model architectures and decoding algor…
Document Level Machine TranslationMachine TranslationTranslation