activity
20192022
most citedLightMBERT: A Simple Yet Effective Method for Multilingual BERT Distillation

5 citations · 8 across the 4 of their papers we have counts for

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5 papers · 1 filter

cs.CL2022

Text is no more Enough! A Benchmark for Profile-based Spoken Language Understanding

Xiao Xu, Libo Qin, Kaiji Chen +3

Current researches on spoken language understanding (SLU) heavily are limited to a simple setting: the plain text-based SLU that takes the user utterance as input and generates its…

cs.CL20215 cited

LightMBERT: A Simple Yet Effective Method for Multilingual BERT Distillation

Xiaoqi Jiao, Yichun Yin, Lifeng Shang +5

The multilingual pre-trained language models (e.g, mBERT, XLM and XLM-R) have shown impressive performance on cross-lingual natural language understanding tasks. However, these mod…

cs.CL20202 cited

Improving Task-Agnostic BERT Distillation with Layer Mapping Search

Xiaoqi Jiao, Huating Chang, Yichun Yin +6

Knowledge distillation (KD) which transfers the knowledge from a large teacher model to a small student model, has been widely used to compress the BERT model recently. Besides the…

cs.CL2019

TinyBERT: Distilling BERT for Natural Language Understanding

Xiaoqi Jiao, Yichun Yin, Lifeng Shang +5

Language model pre-training, such as BERT, has significantly improved the performances of many natural language processing tasks. However, pre-trained language models are usually c…

cs.CL2019

Open Named Entity Modeling from Embedding Distribution

Ying Luo, Hai Zhao, Zhuosheng Zhang +1

In this paper, we report our discovery on named entity distribution in a general word embedding space, which helps an open definition on multilingual named entity definition rather…