13 citations · 22 across the 10 of their papers we have counts for
10 papers · 1 filter
Explainable Topic-Enhanced Argument Mining from Heterogeneous Sources
Jiasheng Si, Yingjie Zhu, Xingyu Shi +2
Given a controversial target such as ``nuclear energy'', argument mining aims to identify the argumentative text from heterogeneous sources. Current approaches focus on exploring b…
Boosting Low-Resource Biomedical QA via Entity-Aware Masking Strategies
Gabriele Pergola, Elena Kochkina, Lin Gui +2
Biomedical question-answering (QA) has gained increased attention for its capability to provide users with high-quality information from a vast scientific literature. Although an i…
CHIME: Cross-passage Hierarchical Memory Network for Generative Review Question Answering
Junru Lu, Gabriele Pergola, Lin Gui +2
We introduce CHIME, a cross-passage hierarchical memory network for question answering (QA) via text generation. It extends XLNet introducing an auxiliary memory module consisting…
A Neural Generative Model for Joint Learning Topics and Topic-Specific Word Embeddings
Lixing Zhu, Yulan He, Deyu Zhou
We propose a novel generative model to explore both local and global context for joint learning topics and topic-specific word embeddings. In particular, we assume that global late…
Neural Topic Modeling with Bidirectional Adversarial Training
Rui Wang, Xuemeng Hu, Deyu Zhou +4
Recent years have witnessed a surge of interests of using neural topic models for automatic topic extraction from text, since they avoid the complicated mathematical derivations fo…
Topical Phrase Extraction from Clinical Reports by Incorporating both Local and Global Context
Gabriele Pergola, Yulan He, David Lowe
Making sense of words often requires to simultaneously examine the surrounding context of a term as well as the global themes characterizing the overall corpus. Several topic model…