6 citations · 8 across the 3 of their papers we have counts for
4 papers · 1 filter
Crisis Domain Adaptation Using Sequence-to-sequence Transformers
Congcong Wang, Paul Nulty, David Lillis
User-generated content (UGC) on social media can act as a key source of information for emergency responders in crisis situations. However, due to the volume concerned, computation…
Transformer-based Multi-task Learning for Disaster Tweet Categorisation
Congcong Wang, Paul Nulty, David Lillis
Social media has enabled people to circulate information in a timely fashion, thus motivating people to post messages seeking help during crisis situations. These messages can cont…
Multi-task transfer learning for finding actionable information from crisis-related messages on social media
Congcong Wang, David Lillis
The Incident streams (IS) track is a research challenge aimed at finding important information from social media during crises for emergency response purposes. More specifically, g…
UCD-CS at W-NUT 2020 Shared Task-3: A Text to Text Approach for COVID-19 Event Extraction on Social Media
Congcong Wang, David Lillis
In this paper, we describe our approach in the shared task: COVID-19 event extraction from Twitter. The objective of this task is to extract answers from COVID-related tweets to a…