2 citations · 5 across the 6 of their papers we have counts for
6 papers
LUNA: Language Understanding with Number Augmentations on Transformers via Number Plugins and Pre-training
Hongwei Han, Jialiang Xu, Mengyu Zhou +3
Transformers are widely used in NLP tasks. However, current approaches to leveraging transformers to understand language expose one weak spot: Number understanding. In some scenari…
VarMAE: Pre-training of Variational Masked Autoencoder for Domain-adaptive Language Understanding
Dou Hu, Xiaolong Hou, Xiyang Du +4
Pre-trained language models have achieved promising performance on general benchmarks, but underperform when migrated to a specific domain. Recent works perform pre-training from s…
PALI-NLP at SemEval-2022 Task 4: Discriminative Fine-tuning of Transformers for Patronizing and Condescending Language Detection
Dou Hu, Mengyuan Zhou, Xiyang Du +5
Patronizing and condescending language (PCL) has a large harmful impact and is difficult to detect, both for human judges and existing NLP systems. At SemEval-2022 Task 4, we propo…
Sequential Attention Module for Natural Language Processing
Mengyuan Zhou, Jian Ma, Haiqin Yang +2
Recently, large pre-trained neural language models have attained remarkable performance on many downstream natural language processing (NLP) applications via fine-tuning. In this p…
Sattiy at SemEval-2021 Task 9: An Ensemble Solution for Statement Verification and Evidence Finding with Tables
Xiaoyi Ruan, Meizhi Jin, Jian Ma +4
Question answering from semi-structured tables can be seen as a semantic parsing task and is significant and practical for pushing the boundary of natural language understanding. E…
MagicPai at SemEval-2021 Task 7: Method for Detecting and Rating Humor Based on Multi-Task Adversarial Training
Jian Ma, Shuyi Xie, Haiqin Yang +4
This paper describes MagicPai's system for SemEval 2021 Task 7, HaHackathon: Detecting and Rating Humor and Offense. This task aims to detect whether the text is humorous and how h…