6 citations · 11 across the 4 of their papers we have counts for
8 papers
Opinion Tree Parsing for Aspect-based Sentiment Analysis
Xiaoyi Bao, Xiaotong Jiang, Zhongqing Wang +2
Extracting sentiment elements using pre-trained generative models has recently led to large improvements in aspect-based sentiment analysis benchmarks. However, these models always…
Coreference Resolution: Are the eliminated spans totally worthless?
Xin Tan, Longyin Zhang, Guodong Zhou
Various neural-based methods have been proposed so far for joint mention detection and coreference resolution. However, existing works on coreference resolution are mainly dependen…
Improving AMR Parsing with Sequence-to-Sequence Pre-training
Dongqin Xu, Junhui Li, Muhua Zhu +2
In the literature, the research on abstract meaning representation (AMR) parsing is much restricted by the size of human-curated dataset which is critical to build an AMR parser wi…
A Discrete CVAE for Response Generation on Short-Text Conversation
Jun Gao, Wei Bi, Xiaojiang Liu +3
Neural conversation models such as encoder-decoder models are easy to generate bland and generic responses. Some researchers propose to use the conditional variational autoencoder(…
Human-Like Decision Making: Document-level Aspect Sentiment Classification via Hierarchical Reinforcement Learning
Jingjing Wang, Changlong Sun, Shoushan Li +5
Recently, neural networks have shown promising results on Document-level Aspect Sentiment Classification (DASC). However, these approaches often offer little transparency w.r.t. th…
Modeling Graph Structure in Transformer for Better AMR-to-Text Generation
Jie Zhu, Junhui Li, Muhua Zhu +3
Recent studies on AMR-to-text generation often formalize the task as a sequence-to-sequence (seq2seq) learning problem by converting an Abstract Meaning Representation (AMR) graph…