LMVE at SemEval-2020 Task 4: Commonsense Validation and Explanation using Pretraining Language Model

6 July 2020

Papers citing "LMVE at SemEval-2020 Task 4: Commonsense Validation and Explanation using Pretraining Language Model"

7 / 7 papers shown

Title
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations Zhenzhong Lan Mingda Chen Sebastian Goodman Kevin Gimpel Piyush Sharma Radu Soricut SSL AIMat 373 6,467 0 26 Sep 2019
SpanBERT: Improving Pre-training by Representing and Predicting Spans Mandar Joshi Danqi Chen Yinhan Liu Daniel S. Weld Luke Zettlemoyer Omer Levy 153 1,967 0 24 Jul 2019
Does It Make Sense? And Why? A Pilot Study for Sense Making and Explanation Cunxiang Wang Shuailong Liang Yue Zhang Xiaonan Li Tian Gao LRM 61 111 0 02 Jun 2019
Subword Regularization: Improving Neural Network Translation Models with Multiple Subword Candidates Taku Kudo 226 1,173 0 29 Apr 2018
Deep contextualized word representations Matthew E. Peters Mark Neumann Mohit Iyyer Matt Gardner Christopher Clark Kenton Lee Luke Zettlemoyer NAI 230 11,566 0 15 Feb 2018
SQuAD: 100,000+ Questions for Machine Comprehension of Text Pranav Rajpurkar Jian Zhang Konstantin Lopyrev Percy Liang RALM 312 8,169 0 16 Jun 2016
A large annotated corpus for learning natural language inference Samuel R. Bowman Gabor Angeli Christopher Potts Christopher D. Manning 324 4,293 0 21 Aug 2015