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01/28/2022
Towards a Broad Coverage Named Entity Resource: A Data-Efficient Approach for Many Diverse Languages
Parallel corpora are ideal for extracting a multilingual named entity (M...
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09/20/2021
BERT Cannot Align Characters
In previous work, it has been shown that BERT can adequately align cross...
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09/16/2021
Locating Language-Specific Information in Contextualized Embeddings
Multilingual pretrained language models (MPLMs) exhibit multilinguality ...
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09/13/2021
Graph Algorithms for Multiparallel Word Alignment
With the advent of end-to-end deep learning approaches in machine transl...
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09/13/2021
Wine is Not v i n. – On the Compatibility of Tokenizations Across Languages
The size of the vocabulary is a central design choice in large pretraine...
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07/14/2021
ParCourE: A Parallel Corpus Explorer for a Massively Multilingual Corpus
With more than 7000 languages worldwide, multilingual natural language p...
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04/14/2021
Static Embeddings as Efficient Knowledge Bases?
Recent research investigates factual knowledge stored in large pretraine...
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02/22/2021
Position Information in Transformers: An Overview
Transformers are arguably the main workhorse in recent Natural Language ...
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02/01/2021
Multilingual LAMA: Investigating Knowledge in Multilingual Pretrained Language Models
Recently, it has been found that monolingual English language models can...
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12/21/2020
Subword Sampling for Low Resource Word Alignment
Annotation projection is an important area in NLP that can greatly contr...
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06/16/2020
Modeling Graph Structure via Relative Position for Better Text Generation from Knowledge Graphs
We present a novel encoder-decoder architecture for graph-to-text genera...
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05/01/2020
Identifying Necessary Elements for BERT's Multilinguality
It has been shown that multilingual BERT (mBERT) yields high quality mul...
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04/25/2020
Quantifying the Contextualization of Word Representations with Semantic Class Probing
Pretrained language models have achieved a new state of the art on many ...
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04/18/2020
SimAlign: High Quality Word Alignments without Parallel Training Data using Static and Contextualized Embeddings
Word alignments are useful for tasks like statistical and neural machine...
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04/18/2019
Analytical Methods for Interpretable Ultradense Word Embeddings
Word embeddings are useful for a wide variety of tasks, but they lack in...
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11/01/2018
A Stronger Baseline for Multilingual Word Embeddings
Levy, Søgaard and Goldberg's (2017) S-ID (sentence ID) method applies wo...
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01/21/2018
