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 ...
|
|
|
|
Abstract:
Cross-lingual document representations enable language understanding in multilingual contexts and allow transfer learning from high-resource to low-resource languages at the document level. Recently large pre-trained language models such as BERT, XLM and XLM-RoBERTa have achieved great success when fine-tuned on sentence-level downstream tasks. It is tempting to apply these cross-lingual models to document representation learning. However, there are two challenges: (1) these models impose high costs on long document processing and thus many of them have strict length limit; (2) model fine-tuning requires extra data and computational resources, which is not practical in resource-limited settings. In this work, we address these challenges by proposing unsupervised Language-Agnostic Weighted Document Representations (LAWDR). We study the geometry of pre-trained sentence embeddings and leverage it to derive document representations without fine-tuning. Evaluated on cross-lingual document alignment, LAWDR ...
|
|
Keyword:
Artificial Intelligence cs.AI; Computation and Language cs.CL; FOS Computer and information sciences
|
|
URL: https://dx.doi.org/10.48550/arxiv.2106.03379 https://arxiv.org/abs/2106.03379
|
|
BASE
|
|
Hide 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)
|
|
BASE
|
|
Show 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
|
|
|
|