2 citations · 4 across the 9 of their papers we have counts for
10 papers
Beyond surface form: A pipeline for semantic analysis in Alzheimer's Disease detection from spontaneous speech
Dylan Phelps, Rodrigo Wilkens, Edward Gow-Smith +6
Alzheimer's Disease (AD) is a progressive neurodegenerative condition that adversely affects cognitive abilities. Language-related changes can be automatically identified through t…
Stands to Reason: Investigating the Effect of Reasoning on Idiomaticity Detection
Dylan Phelps, Rodrigo Wilkens, Edward Gow-Smith +3
The recent trend towards utilisation of reasoning models has improved the performance of Large Language Models (LLMs) across many tasks which involve logical steps. One linguistic…
Limitations of Religious Data and the Importance of the Target Domain: Towards Machine Translation for Guinea-Bissau Creole
Jacqueline Rowe, Edward Gow-Smith, Mark Hepple
We introduce a new dataset for machine translation of Guinea-Bissau Creole (Kiriol), comprising around 40 thousand parallel sentences to English and Portuguese. This dataset is mad…
Sign of the Times: Evaluating the use of Large Language Models for Idiomaticity Detection
Dylan Phelps, Thomas Pickard, Maggie Mi +2
Despite the recent ubiquity of large language models and their high zero-shot prompted performance across a wide range of tasks, it is still not known how well they perform on task…
Word Boundary Information Isn't Useful for Encoder Language Models
Edward Gow-Smith, Dylan Phelps, Harish Tayyar Madabushi +2
All existing transformer-based approaches to NLP using subword tokenisation algorithms encode whitespace (word boundary information) through the use of special space symbols (such…
Use of Transformer-Based Models for Word-Level Transliteration of the Book of the Dean of Lismore
Edward Gow-Smith, Mark McConville, William Gillies +2
The Book of the Dean of Lismore (BDL) is a 16th-century Scottish Gaelic manuscript written in a non-standard orthography. In this work, we outline the problem of transliterating th…
SemEval-2022 Task 2: Multilingual Idiomaticity Detection and Sentence Embedding
Harish Tayyar Madabushi, Edward Gow-Smith, Marcos Garcia +3
This paper presents the shared task on Multilingual Idiomaticity Detection and Sentence Embedding, which consists of two subtasks: (a) a binary classification task aimed at identif…
Sample Efficient Approaches for Idiomaticity Detection
Dylan Phelps, Xuan-Rui Fan, Edward Gow-Smith +3
Deep neural models, in particular Transformer-based pre-trained language models, require a significant amount of data to train. This need for data tends to lead to problems when de…
Improving Tokenisation by Alternative Treatment of Spaces
Edward Gow-Smith, Harish Tayyar Madabushi, Carolina Scarton +1
Tokenisation is the first step in almost all NLP tasks, and state-of-the-art transformer-based language models all use subword tokenisation algorithms to process input text. Existi…
AStitchInLanguageModels: Dataset and Methods for the Exploration of Idiomaticity in Pre-Trained Language Models
Harish Tayyar Madabushi, Edward Gow-Smith, Carolina Scarton +1
Despite their success in a variety of NLP tasks, pre-trained language models, due to their heavy reliance on compositionality, fail in effectively capturing the meanings of multiwo…