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20192023
most citedGlyce: Glyph-vectors for Chinese Character Representations

147 citations · 589 across the 17 of their papers we have counts for

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Showing 2019Show all

6 papers · 1 filter

cs.CL2019★ 32 cited

Dice Loss for Data-imbalanced NLP Tasks

Xiaoya Li, Xiaofei Sun, Yuxian Meng +4

Many NLP tasks such as tagging and machine reading comprehension are faced with the severe data imbalance issue: negative examples significantly outnumber positive examples, and th…

cs.CL2019★ 8 cited

Large-scale Pretraining for Neural Machine Translation with Tens of Billions of Sentence Pairs

Yuxian Meng, Xiangyuan Ren, Zijun Sun +4

In this paper, we investigate the problem of training neural machine translation (NMT) systems with a dataset of more than 40 billion bilingual sentence pairs, which is larger than…

cs.CL2019★ 51 cited

A Unified MRC Framework for Named Entity Recognition

Xiaoya Li, Jingrong Feng, Yuxian Meng +4

The task of named entity recognition (NER) is normally divided into nested NER and flat NER depending on whether named entities are nested or not. Models are usually separately dev…

cs.CL2019★ 1 cited

Query-Based Named Entity Recognition

Yuxian Meng, Xiaoya Li, Zijun Sun +1

In this paper, we propose a new strategy for the task of named entity recognition (NER). We cast the task as a query-based machine reading comprehension task: e.g., the task of ext…

cs.CL2019★ 20 cited

Is Word Segmentation Necessary for Deep Learning of Chinese Representations?

Xiaoya Li, Yuxian Meng, Xiaofei Sun +3

Segmenting a chunk of text into words is usually the first step of processing Chinese text, but its necessity has rarely been explored. In this paper, we ask the fundamental questi…

cs.CL2019★ 147 cited

Glyce: Glyph-vectors for Chinese Character Representations

Yuxian Meng, Wei Wu, Fei Wang +8

It is intuitive that NLP tasks for logographic languages like Chinese should benefit from the use of the glyph information in those languages. However, due to the lack of rich pict…