62 citations · 130 across the 40 of their papers we have counts for
10 papers · 1 filter
Unsupervised Learning of Discourse Structures using a Tree Autoencoder
Patrick Huber, Giuseppe Carenini
Discourse information, as postulated by popular discourse theories, such as RST and PDTB, has been shown to improve an increasing number of downstream NLP tasks, showing positive e…
Do We Really Need That Many Parameters In Transformer For Extractive Summarization? Discourse Can Help !
Wen Xiao, Patrick Huber, Giuseppe Carenini
The multi-head self-attention of popular transformer models is widely used within Natural Language Processing (NLP), including for the task of extractive summarization. With the go…
Systematically Exploring Redundancy Reduction in Summarizing Long Documents
Wen Xiao, Giuseppe Carenini
Our analysis of large summarization datasets indicates that redundancy is a very serious problem when summarizing long documents. Yet, redundancy reduction has not been thoroughly…
Unleashing the Power of Neural Discourse Parsers -- A Context and Structure Aware Approach Using Large Scale Pretraining
Grigorii Guz, Patrick Huber, Giuseppe Carenini
RST-based discourse parsing is an important NLP task with numerous downstream applications, such as summarization, machine translation and opinion mining. In this paper, we demonst…
From Sentiment Annotations to Sentiment Prediction through Discourse Augmentation
Patrick Huber, Giuseppe Carenini
Sentiment analysis, especially for long documents, plausibly requires methods capturing complex linguistics structures. To accommodate this, we propose a novel framework to exploit…
MEGA RST Discourse Treebanks with Structure and Nuclearity from Scalable Distant Sentiment Supervision
Patrick Huber, Giuseppe Carenini
The lack of large and diverse discourse treebanks hinders the application of data-driven approaches, such as deep-learning, to RST-style discourse parsing. In this work, we present…
An Improved Attention for Visual Question Answering
Tanzila Rahman, Shih-Han Chou, Leonid Sigal +1
We consider the problem of Visual Question Answering (VQA). Given an image and a free-form, open-ended, question, expressed in natural language, the goal of VQA system is to provid…
Improving Context Modeling in Neural Topic Segmentation
Linzi Xing, Brad Hackinen, Giuseppe Carenini +1
Topic segmentation is critical in key NLP tasks and recent works favor highly effective neural supervised approaches. However, current neural solutions are arguably limited in how…
Neural RST-based Evaluation of Discourse Coherence
Grigorii Guz, Peyman Bateni, Darius Muglich +1
This paper evaluates the utility of Rhetorical Structure Theory (RST) trees and relations in discourse coherence evaluation. We show that incorporating silver-standard RST features…
Exploratory Analysis of COVID-19 Related Tweets in North America to Inform Public Health Institutes
Hyeju Jang, Emily Rempel, Giuseppe Carenini +1
Social media is a rich source where we can learn about people's reactions to social issues. As COVID-19 has significantly impacted on people's lives, it is essential to capture how…