6 citations · 11 across the 21 of their papers we have counts for
12 papers
A Predictive Factor Analysis of Social Biases and Task-Performance in Pretrained Masked Language Models
Yi Zhou, Jose Camacho-Collados, Danushka Bollegala
Various types of social biases have been reported with pretrained Masked Language Models (MLMs) in prior work. However, multiple underlying factors are associated with an MLM such…
Can Word Sense Distribution Detect Semantic Changes of Words?
Xiaohang Tang, Yi Zhou, Taichi Aida +2
Semantic Change Detection (SCD) of words is an important task for various NLP applications that must make time-sensitive predictions. Some words are used over time in novel ways to…
-- Predicting the Semantic Changes in Words across Corpora by Context Swapping
Taichi Aida, Danushka Bollegala
Meanings of words change over time and across domains. Detecting the semantic changes of words is an important task for various NLP applications that must make time-sensitive predi…
Together We Make Sense -- Learning Meta-Sense Embeddings from Pretrained Static Sense Embeddings
Haochen Luo, Yi Zhou, Danushka Bollegala
Sense embedding learning methods learn multiple vectors for a given ambiguous word, corresponding to its different word senses. For this purpose, different methods have been propos…
Metrics for quantifying isotropy in high dimensional unsupervised clustering tasks in a materials context
Samantha Durdy, Michael W. Gaultois, Vladimir Gusev +2
Clustering is a common task in machine learning, but clusters of unlabelled data can be hard to quantify. The application of clustering algorithms in chemistry is often dependant o…
Solving Cosine Similarity Underestimation between High Frequency Words by L2 Norm Discounting
Saeth Wannasuphoprasit, Yi Zhou, Danushka Bollegala
Cosine similarity between two words, computed using their contextualised token embeddings obtained from masked language models (MLMs) such as BERT has shown to underestimate the ac…