no code implementations • 15 Sep 2017 • Yang Li, Quan Pan, Suhang Wang, Haiyun Peng, Tao Yang, Erik Cambria
The majority of existing semi-supervised VAEs utilize a classifier to exploit label information, where the parameters of the classifier are introduced to the VAE.
no code implementations • The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18) 2018 • Yukun Ma, Haiyun Peng, Erik Cambria
Analyzing people’s opinions and sentiments towards certain aspects is an important task of natural language understanding.
Ranked #4 on Aspect-Based Sentiment Analysis (ABSA) on Sentihood
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +3
no code implementations • 23 Jan 2019 • Navonil Majumder, Soujanya Poria, Haiyun Peng, Niyati Chhaya, Erik Cambria, Alexander Gelbukh
We argue that knowledge in sarcasm detection can also be beneficial to sentiment classification and vice versa.
no code implementations • 23 Jan 2019 • Haiyun Peng, Yukun Ma, Soujanya Poria, Yang Li, Erik Cambria
Furthermore, we also fuse phonetic features with textual and visual features in order to mimic the way humans read and understand Chinese text.
5 code implementations • ACL 2019 • Wei Zhao, Haiyun Peng, Steffen Eger, Erik Cambria, Min Yang
Obstacles hindering the development of capsule networks for challenging NLP applications include poor scalability to large output spaces and less reliable routing processes.
Ranked #1 on Text Classification on RCV1 (P@1 metric)
6 code implementations • 5 Nov 2019 • Haiyun Peng, Lu Xu, Lidong Bing, Fei Huang, Wei Lu, Luo Si
In this paper, we introduce a new subtask under ABSA, named aspect sentiment triplet extraction (ASTE).
Ranked #5 on Aspect Sentiment Triplet Extraction on SemEval
1 code implementation • EMNLP 2021 • Wenxuan Zhang, Ruidan He, Haiyun Peng, Lidong Bing, Wai Lam
Many efforts have been made in solving the Aspect-based sentiment analysis (ABSA) task.
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +1