2 citations · 5 across the 11 of their papers we have counts for
14 papers · 1 filter
Towards Domain-Independent Supervised Discourse Parsing Through Gradient Boosting
Patrick Huber, Giuseppe Carenini
Discourse analysis and discourse parsing have shown great impact on many important problems in the field of Natural Language Processing (NLP). Given the direct impact of discourse…
Unsupervised Inference of Data-Driven Discourse Structures using a Tree Auto-Encoder
Patrick Huber, Giuseppe Carenini
With a growing need for robust and general discourse structures in many downstream tasks and real-world applications, the current lack of high-quality, high-quantity discourse tree…
Improving Topic Segmentation by Injecting Discourse Dependencies
Linzi Xing, Patrick Huber, Giuseppe Carenini
Recent neural supervised topic segmentation models achieve distinguished superior effectiveness over unsupervised methods, with the availability of large-scale training corpora sam…
Towards Understanding Large-Scale Discourse Structures in Pre-Trained and Fine-Tuned Language Models
Patrick Huber, Giuseppe Carenini
With a growing number of BERTology work analyzing different components of pre-trained language models, we extend this line of research through an in-depth analysis of discourse inf…
W-RST: Towards a Weighted RST-style Discourse Framework
Patrick Huber, Wen Xiao, Giuseppe Carenini
Aiming for a better integration of data-driven and linguistically-inspired approaches, we explore whether RST Nuclearity, assigning a binary assessment of importance between text s…
Predicting Discourse Trees from Transformer-based Neural Summarizers
Wen Xiao, Patrick Huber, Giuseppe Carenini
Previous work indicates that discourse information benefits summarization. In this paper, we explore whether this synergy between discourse and summarization is bidirectional, by i…