activity
20202022
most citedCOVID-SEE: Scientific Evidence Explorer for COVID-19 Related Research

12 citations · 22 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL20224 cited

Not another Negation Benchmark: The NaN-NLI Test Suite for Sub-clausal Negation

Thinh Hung Truong, Yulia Otmakhova, Timothy Baldwin +3

Negation is poorly captured by current language models, although the extent of this problem is not widely understood. We introduce a natural language inference (NLI) test suite to…

cs.CL20222 cited

LED down the rabbit hole: exploring the potential of global attention for biomedical multi-document summarisation

Yulia Otmakhova, Hung Thinh Truong, Timothy Baldwin +3

In this paper we report on our submission to the Multidocument Summarisation for Literature Review (MSLR) shared task. Specifically, we adapt PRIMERA (Xiao et al., 2022) to the bio…

cs.CL20224 cited

ITTC @ TREC 2021 Clinical Trials Track

Thinh Hung Truong, Yulia Otmakhova, Rahmad Mahendra +6

This paper describes the submissions of the Natural Language Processing (NLP) team from the Australian Research Council Industrial Transformation Training Centre (ITTC) for Cogniti…

cs.CL2021

Impact of detecting clinical trial elements in exploration of COVID-19 literature

Simon Šuster, Karin Verspoor, Timothy Baldwin +4

The COVID-19 pandemic has driven ever-greater demand for tools which enable efficient exploration of biomedical literature. Although semi-structured information resulting from conc…

cs.CL202012 cited

COVID-SEE: Scientific Evidence Explorer for COVID-19 Related Research

Karin Verspoor, Simon Šuster, Yulia Otmakhova +7

We present COVID-SEE, a system for medical literature discovery based on the concept of information exploration, which builds on several distinct text analysis and natural language…