most citedSequential Attention Module for Natural Language Processing

2 citations · 2 across the 2 of their papers we have counts for

collaborators

5 papers

cs.AI20212 cited

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…

cs.CL2021

RefBERT: Compressing BERT by Referencing to Pre-computed Representations

Xinyi Wang, Haiqin Yang, Liang Zhao +2

Recently developed large pre-trained language models, e.g., BERT, have achieved remarkable performance in many downstream natural language processing applications. These pre-traine…

cs.AI2021

PALI at SemEval-2021 Task 2: Fine-Tune XLM-RoBERTa for Word in Context Disambiguation

Shuyi Xie, Jian Ma, Haiqin Yang +3

This paper presents the PALI team's winning system for SemEval-2021 Task 2: Multilingual and Cross-lingual Word-in-Context Disambiguation. We fine-tune XLM-RoBERTa model to solve t…

cs.AI2021

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…

cs.AI2021

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…