68 citations · 218 across the 63 of their papers we have counts for
12 papers · 1 filter
Exploring Text Specific and Blackbox Fairness Algorithms in Multimodal Clinical NLP
John Chen, Ian Berlot-Attwell, Safwan Hossain +2
Clinical machine learning is increasingly multimodal, collected in both structured tabular formats and unstructured forms such as freetext. We propose a novel task of exploring fai…
Semantic coordinates analysis reveals language changes in the AI field
Zining Zhu, Yang Xu, Frank Rudzicz
Semantic shifts can reflect changes in beliefs across hundreds of years, but it is less clear whether trends in fast-changing communities across a short time can be detected. We pr…
On Losses for Modern Language Models
Stephane Aroca-Ouellette, Frank Rudzicz
BERT set many state-of-the-art results over varied NLU benchmarks by pre-training over two tasks: masked language modelling (MLM) and next sentence prediction (NSP), the latter of…
Examining the rhetorical capacities of neural language models
Zining Zhu, Chuer Pan, Mohamed Abdalla +1
Recently, neural language models (LMs) have demonstrated impressive abilities in generating high-quality discourse. While many recent papers have analyzed the syntactic aspects enc…
Word class flexibility: A deep contextualized approach
Bai Li, Guillaume Thomas, Yang Xu +1
Word class flexibility refers to the phenomenon whereby a single word form is used across different grammatical categories. Extensive work in linguistic typology has sought to char…
An information theoretic view on selecting linguistic probes
Zining Zhu, Frank Rudzicz
There is increasing interest in assessing the linguistic knowledge encoded in neural representations. A popular approach is to attach a diagnostic classifier -- or "probe" -- to pe…
Ethics of Artificial Intelligence in Surgery
Frank Rudzicz, Raeid Saqur
Here we discuss the four key principles of bio-medical ethics from surgical context. We elaborate on the definition of 'fairness' and its implications in AI system design, with tax…
To BERT or Not To BERT: Comparing Speech and Language-based Approaches for Alzheimer's Disease Detection
Aparna Balagopalan, Benjamin Eyre, Frank Rudzicz +1
Research related to automatically detecting Alzheimer's disease (AD) is important, given the high prevalence of AD and the high cost of traditional methods. Since AD significantly…
Sequential Explanations with Mental Model-Based Policies
Arnold YS Yeung, Shalmali Joshi, Joseph Jay Williams +1
The act of explaining across two parties is a feedback loop, where one provides information on what needs to be explained and the other provides an explanation relevant to this inf…
Speaker diarization with session-level speaker embedding refinement using graph neural networks
Jixuan Wang, Xiong Xiao, Jian Wu +3
Deep speaker embedding models have been commonly used as a building block for speaker diarization systems; however, the speaker embedding model is usually trained according to a gl…
Identification of primary and collateral tracks in stuttered speech
Rachid Riad, Anne-Catherine Bachoud-Lévi, Frank Rudzicz +1
Disfluent speech has been previously addressed from two main perspectives: the clinical perspective focusing on diagnostic, and the Natural Language Processing (NLP) perspective ai…
The Ground Truth Trade-Off in Wearable Sensing Studies
Daniyal Liaqat, Robert Wu, Salaar Liaqat +3
Perez et al's study using the Apple Watch to identify atrial fibrillation (AF) is a watershed moment in large-scale machine learning for wearable computing. Identifying relevant pa…