151 citations · 318 across the 14 of their papers we have counts for
22 papers
A Pipeline for Generating, Annotating and Employing Synthetic Data for Real World Question Answering
Matthew Maufe, James Ravenscroft, Rob Procter +1
Question Answering (QA) is a growing area of research, often used to facilitate the extraction of information from within documents. State-of-the-art QA models are usually pre-trai…
Evaluation of Abstractive Summarisation Models with Machine Translation in Deliberative Processes
M. Arana-Catania, Rob Procter, Yulan He +1
We present work on summarising deliberative processes for non-English languages. Unlike commonly studied datasets, such as news articles, this deliberation dataset reflects difficu…
Citizen Participation and Machine Learning for a Better Democracy
M. Arana-Catania, F. A. Van Lier, Rob Procter +4
The development of democratic systems is a crucial task as confirmed by its selection as one of the Millennium Sustainable Development Goals by the United Nations. In this article,…
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…
CD2CR: Co-reference Resolution Across Documents and Domains
James Ravenscroft, Arie Cattan, Amanda Clare +2
Cross-document co-reference resolution (CDCR) is the task of identifying and linking mentions to entities and concepts across many text documents. Current state-of-the-art models f…
QMUL-SDS @ DIACR-Ita: Evaluating Unsupervised Diachronic Lexical Semantics Classification in Italian
Rabab Alkhalifa, Adam Tsakalidis, Arkaitz Zubiaga +1
In this paper, we present the results and main findings of our system for the DIACR-ITA 2020 Task. Our system focuses on using variations of training sets and different semantic de…