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The CoNLL-2013 Shared Task on Grammatical Error Correction
TLDR
The CoNLL-2014 shared task was devoted to grammatical error correction of all error types, instead of just the five error types. Expand
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Improved Word Sense Disambiguation Using Pre-Trained Contextualized Word Representations
TLDR
In this paper, we explore different strategies of integrating pre-trained contextualized word representations and our best strategy achieves accuracies exceeding the best prior published accuracies by significant margins. Expand
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A Dependency-Based Neural Reordering Model for Statistical Machine Translation
TLDR
We present a novel reordering approach utilizing a neural network and dependency-based embeddings to predict whether the translations of two source words linked by a dependency relation should remain in the same order or should be swapped in the translated sentence. Expand
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To Swap or Not to Swap? Exploiting Dependency Word Pairs for Reordering in Statistical Machine Translation
TLDR
In this paper, we present a novel reordering approach utilizing sparse features based on dependency word pairs. Expand
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Syntax-Based Statistical Machine Translation
TLDR
In its early development, machine translation adopted rule-based approaches, without the use of language syntax. Expand
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Upping the Ante: Towards a Better Benchmark for Chinese-to-English Machine Translation
TLDR
We propose a benchmark in evaluation setup for Chinese-to-English machine translation, such that the effectiveness of a new proposed MT approach can be directly compared to previous approaches. Expand
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