2 citations · 2 across the 6 of their papers we have counts for
7 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…
From Input Perception to Predictive Insight: Modeling Model Blind Spots Before They Become Errors
Maggie Mi, Aline Villavicencio, Nafise Sadat Moosavi
Language models often struggle with idiomatic, figurative, or context-sensitive inputs, not because they produce flawed outputs, but because they misinterpret the input from the ou…
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…
Rolling the DICE on Idiomaticity: How LLMs Fail to Grasp Context
Maggie Mi, Aline Villavicencio, Nafise Sadat Moosavi
Human processing of idioms relies on understanding the contextual sentences in which idioms occur, as well as language-intrinsic features such as frequency and speaker-intrinsic fa…
A Methodology for Explainable Large Language Models with Integrated Gradients and Linguistic Analysis in Text Classification
Marina Ribeiro, Bárbara Malcorra, Natália B. Mota +4
Neurological disorders that affect speech production, such as Alzheimer's Disease (AD), significantly impact the lives of both patients and caregivers, whether through social, psyc…
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…