SOTAVerified

Document Level Machine Translation

Papers

Showing 2650 of 58 papers

TitleStatusHype
Modeling Context With Linear Attention for Scalable Document-Level TranslationCode0
Revamping Multilingual Agreement Bidirectionally via Switched Back-translation for Multilingual Neural Machine Translation0
TANDO: A Corpus for Document-level Machine TranslationCode0
DELA Project: Document-level Machine Translation Evaluation0
Learn To Remember: Transformer with Recurrent Memory for Document-Level Machine Translation0
Locality-Sensitive Hashing for Long Context Neural Machine Translation0
BlonDe: An Automatic Evaluation Metric for Document-level Machine Translation0
Document-level Neural Machine Translation Using Dependency RST Structure0
SMDT: Selective Memory-Augmented Neural Document Translation0
Document Level Hierarchical Transformer0
Contrastive Learning for Context-aware Neural Machine Translation Using Coreference Information0
Contrastive Learning for Context-aware Neural Machine TranslationUsing Coreference Information0
Multi-Hop Transformer for Document-Level Machine Translation0
Hierarchical Learning for Generation with Long Source Sequences0
Towards Personalised and Document-level Machine Translation of Dialogue0
Towards Personalised and Document-level Machine Translation of Dialogue0
A Comparison of Approaches to Document-level Machine Translation0
Improving NMT via Filtered Back Translation0
Document-Level Neural Machine Translation Using BERT as Context Encoder0
Document-Level Machine Translation Evaluation Project: Methodology, Effort and Inter-Annotator Agreement0
Leveraging Discourse Rewards for Document-Level Neural Machine Translation0
A Simple and Effective Unified Encoder for Document-Level Machine Translation0
Corpora for Document-Level Neural Machine Translation0
Learning Contextualized Sentence Representations for Document-Level Neural Machine Translation0
Hierarchical Modeling of Global Context for Document-Level Neural Machine Translation0
Show:102550
← PrevPage 2 of 3Next →

No leaderboard results yet.