1 citations · 2 across the 4 of their papers we have counts for
5 papers
Towards Structure-aware Paraphrase Identification with Phrase Alignment Using Sentence Encoders
Qiwei Peng, David Weir, Julie Weeds
Previous works have demonstrated the effectiveness of utilising pre-trained sentence encoders based on their sentence representations for meaning comparison tasks. Though such repr…
Representing Syntax and Composition with Geometric Transformations
Lorenzo Bertolini, Julie Weeds, David Weir +1
The exploitation of syntactic graphs (SyGs) as a word's context has been shown to be beneficial for distributional semantic models (DSMs), both at the level of individual word repr…
Data Augmentation for Hypernymy Detection
Thomas Kober, Julie Weeds, Lorenzo Bertolini +1
The automatic detection of hypernymy relationships represents a challenging problem in NLP. The successful application of state-of-the-art supervised approaches using distributed r…
Data Mining in Clinical Trial Text: Transformers for Classification and Question Answering Tasks
Lena Schmidt, Julie Weeds, Julian P. T. Higgins
This research on data extraction methods applies recent advances in natural language processing to evidence synthesis based on medical texts. Texts of interest include abstracts of…
One Representation per Word - Does it make Sense for Composition?
Thomas Kober, Julie Weeds, John Wilkie +2
In this paper, we investigate whether an a priori disambiguation of word senses is strictly necessary or whether the meaning of a word in context can be disambiguated through compo…