1 |
The FLORES-101 Evaluation Benchmark for Low-Resource and Multilingual Machine Translation ...
|
|
|
|
BASE
|
|
Show details
|
|
2 |
LAWDR: Language-Agnostic Weighted Document Representations from Pre-trained Models ...
|
|
|
|
BASE
|
|
Show details
|
|
3 |
Classification-based Quality Estimation: Small and Efficient Models for Real-world Applications ...
|
|
|
|
BASE
|
|
Show details
|
|
5 |
Findings of the AmericasNLP 2021 Shared Task on Open Machine Translation for Indigenous Languages of the Americas ...
|
|
|
|
BASE
|
|
Show details
|
|
6 |
Alternative Input Signals Ease Transfer in Multilingual Machine Translation ...
|
|
|
|
BASE
|
|
Show details
|
|
7 |
Adapting High-resource NMT Models to Translate Low-resource Related Languages without Parallel Data ...
|
|
|
|
BASE
|
|
Show details
|
|
8 |
Findings of the WMT 2021 Shared Task on Quality Estimation ...
|
|
|
|
BASE
|
|
Show details
|
|
9 |
AmericasNLI: Evaluating Zero-shot Natural Language Understanding of Pretrained Multilingual Models in Truly Low-resource Languages ...
|
|
|
|
BASE
|
|
Show details
|
|
10 |
Findings of the WMT 2021 shared task on quality estimation
|
|
|
|
In: 689 ; 730 (2021)
|
|
Abstract:
© (2021) The Authors. Published by ACL. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: http://www.statmt.org/wmt21/pdf/2021.wmt-1.71.pdf ; We report the results of the WMT 2021 shared task on Quality Estimation, where the challenge is to predict the quality of the output of neural machine translation systems at the word and sentence levels. This edition focused on two main novel additions: (i) prediction for unseen languages, i.e. zero-shot settings, and (ii) prediction of sentences with catastrophic errors. In addition, new data was released for a number of languages, especially post-edited data. Participating teams from 19 institutions submitted altogether 1263 systems to different task variants and language pairs.
|
|
Keyword:
machine translation; quality estimation
|
|
URL: http://hdl.handle.net/2436/624392
|
|
BASE
|
|
Hide details
|
|
11 |
Multilingual Translation with Extensible Multilingual Pretraining and Finetuning ...
|
|
|
|
BASE
|
|
Show details
|
|
12 |
MLQE-PE: A Multilingual Quality Estimation and Post-Editing Dataset ...
|
|
|
|
BASE
|
|
Show details
|
|
13 |
Beyond English-Centric Multilingual Machine Translation ...
|
|
|
|
BASE
|
|
Show details
|
|
14 |
Unsupervised quality estimation for neural machine translation
|
|
|
|
In: 8 ; 539 ; 555 (2020)
|
|
BASE
|
|
Show details
|
|
15 |
An exploratory study on multilingual quality estimation
|
|
|
|
In: 366 ; 377 (2020)
|
|
BASE
|
|
Show details
|
|
16 |
BERGAMOT-LATTE submissions for the WMT20 quality estimation shared task
|
|
|
|
In: 1010 ; 1017 (2020)
|
|
BASE
|
|
Show details
|
|
17 |
Findings of the WMT 2020 shared task on quality estimation
|
|
|
|
In: 743 ; 764 (2020)
|
|
BASE
|
|
Show details
|
|
18 |
MLQE-PE: A multilingual quality estimation and post-editing dataset
|
|
|
|
BASE
|
|
Show details
|
|
19 |
Unsupervised Cross-lingual Representation Learning at Scale ...
|
|
|
|
BASE
|
|
Show details
|
|
20 |
WikiMatrix: Mining 135M Parallel Sentences in 1620 Language Pairs from Wikipedia ...
|
|
|
|
BASE
|
|
Show details
|
|
|
|