Discourse processing suffers from data sparsity, especially for dialogue...
Discourse analysis and discourse parsing have shown great impact on many...
With a growing need for robust and general discourse structures in many
...
Recent neural supervised topic segmentation models achieve distinguished...
With a growing number of BERTology work analyzing different components o...
RST-style discourse parsing plays a vital role in many NLP tasks, reveal...
With the rise of large-scale pre-trained language models, open-domain
qu...
Aiming for a better integration of data-driven and linguistically-inspir...
Previous work indicates that discourse information benefits summarizatio...
Discourse information, as postulated by popular discourse theories, such...
The multi-head self-attention of popular transformer models is widely us...
RST-based discourse parsing is an important NLP task with numerous downs...
Sentiment analysis, especially for long documents, plausibly requires me...
The lack of large and diverse discourse treebanks hinders the applicatio...
Discourse parsing could not yet take full advantage of the neural NLP
re...
We present a new recurrent neural network topology to enhance
state-of-t...
We present a new approach to evaluate computational models for the task ...