activity
20182022
most citedVision-and-Language Pretrained Models: A Survey

7 citations · 12 across the 6 of their papers we have counts for

collaborators

11 papers

cs.CV20227 cited

Vision-and-Language Pretrained Models: A Survey

Siqu Long, Feiqi Cao, Soyeon Caren Han +1

Pretrained models have produced great success in both Computer Vision (CV) and Natural Language Processing (NLP). This progress leads to learning joint representations of vision an…

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.CL20211 cited

Progressive Open-Domain Response Generation with Multiple Controllable Attributes

Haiqin Yang, Xiaoyuan Yao, Yiqun Duan +3

It is desirable to include more controllable attributes to enhance the diversity of generated responses in open-domain dialogue systems. However, existing methods can generate resp…

cs.AI2021

Emotion Dynamics Modeling via BERT

Haiqin Yang, Jianping Shen

Emotion dynamics modeling is a significant task in emotion recognition in conversation. It aims to predict conversational emotions when building empathetic dialogue systems. Existi…

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…