activity
20172022
most citedUnderstanding and Improving Layer Normalization

178 citations · 270 across the 11 of their papers we have counts for

collaborators

22 papers

cs.CL20224 cited

Calibrating Factual Knowledge in Pretrained Language Models

Qingxiu Dong, Damai Dai, Yifan Song +3

Previous literature has proved that Pretrained Language Models (PLMs) can store factual knowledge. However, we find that facts stored in the PLMs are not always correct. It motivat…

cs.CL2022

Contextual Representation Learning beyond Masked Language Modeling

Zhiyi Fu, Wangchunshu Zhou, Jingjing Xu +2

How do masked language models (MLMs) such as BERT learn contextual representations? In this work, we analyze the learning dynamics of MLMs. We find that MLMs adopt sampled embeddin…

cs.CL202010 cited

Graph-based Multi-hop Reasoning for Long Text Generation

Liang Zhao, Jingjing Xu, Junyang Lin +3

Long text generation is an important but challenging task.The main problem lies in learning sentence-level semantic dependencies which traditional generative models often suffer fr…

cs.CL201942 cited

MUSE: Parallel Multi-Scale Attention for Sequence to Sequence Learning

Guangxiang Zhao, Xu Sun, Jingjing Xu +2

In sequence to sequence learning, the self-attention mechanism proves to be highly effective, and achieves significant improvements in many tasks. However, the self-attention mecha…

cs.LG2019178 cited

Understanding and Improving Layer Normalization

Jingjing Xu, Xu Sun, Zhiyuan Zhang +2

Layer normalization (LayerNorm) is a technique to normalize the distributions of intermediate layers. It enables smoother gradients, faster training, and better generalization accu…

cs.CL2019

Graph-Based Reasoning over Heterogeneous External Knowledge for Commonsense Question Answering

Shangwen Lv, Daya Guo, Jingjing Xu +7

Commonsense question answering aims to answer questions which require background knowledge that is not explicitly expressed in the question. The key challenge is how to obtain evid…