19 citations · 50 across the 14 of their papers we have counts for
15 papers
Revisiting subword tokenization: A case study on affixal negation in large language models
Thinh Hung Truong, Yulia Otmakhova, Karin Verspoor +2
In this work, we measure the impact of affixal negation on modern English large language models (LLMs). In affixal negation, the negated meaning is expressed through a negative mor…
Principles from Clinical Research for NLP Model Generalization
Aparna Elangovan, Jiayuan He, Yuan Li +1
The NLP community typically relies on performance of a model on a held-out test set to assess generalization. Performance drops observed in datasets outside of official test sets a…
Effects of Human Adversarial and Affable Samples on BERT Generalization
Aparna Elangovan, Jiayuan He, Yuan Li +1
BERT-based models have had strong performance on leaderboards, yet have been demonstrably worse in real-world settings requiring generalization. Limited quantities of training data…
Collective Human Opinions in Semantic Textual Similarity
Yuxia Wang, Shimin Tao, Ning Xie +3
Despite the subjective nature of semantic textual similarity (STS) and pervasive disagreements in STS annotation, existing benchmarks have used averaged human ratings as the gold s…
Language models are not naysayers: An analysis of language models on negation benchmarks
Thinh Hung Truong, Timothy Baldwin, Karin Verspoor +1
Negation has been shown to be a major bottleneck for masked language models, such as BERT. However, whether this finding still holds for larger-sized auto-regressive language model…
Improving Text-based Early Prediction by Distillation from Privileged Time-Series Text
Jinghui Liu, Daniel Capurro, Anthony Nguyen +1
Modeling text-based time-series to make prediction about a future event or outcome is an important task with a wide range of applications. The standard approach is to train and tes…
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…
Cross-modal Clinical Graph Transformer for Ophthalmic Report Generation
Mingjie Li, Wenjia Cai, Karin Verspoor +3
Automatic generation of ophthalmic reports using data-driven neural networks has great potential in clinical practice. When writing a report, ophthalmologists make inferences with…
Improving negation detection with negation-focused pre-training
Thinh Hung Truong, Timothy Baldwin, Trevor Cohn +1
Negation is a common linguistic feature that is crucial in many language understanding tasks, yet it remains a hard problem due to diversity in its expression in different types of…
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…
MPVNN: Mutated Pathway Visible Neural Network Architecture for Interpretable Prediction of Cancer-specific Survival Risk
Gourab Ghosh Roy, Nicholas Geard, Karin Verspoor +1
Survival risk prediction using gene expression data is important in making treatment decisions in cancer. Standard neural network (NN) survival analysis models are black boxes with…
Memorization vs. Generalization: Quantifying Data Leakage in NLP Performance Evaluation
Aparna Elangovan, Jiayuan He, Karin Verspoor
Public datasets are often used to evaluate the efficacy and generalizability of state-of-the-art methods for many tasks in natural language processing (NLP). However, the presence…
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…
Assigning function to protein-protein interactions: a weakly supervised BioBERT based approach using PubMed abstracts
Aparna Elangovan, Melissa Davis, Karin Verspoor
Motivation: Protein-protein interactions (PPI) are critical to the function of proteins in both normal and diseased cells, and many critical protein functions are mediated by inter…
WikiUMLS: Aligning UMLS to Wikipedia via Cross-lingual Neural Ranking
Afshin Rahimi, Timothy Baldwin, Karin Verspoor
We present our work on aligning the Unified Medical Language System (UMLS) to Wikipedia, to facilitate manual alignment of the two resources. We propose a cross-lingual neural rera…