most citedRobustness and Reliability of Gender Bias Assessment in Word Embeddings: The Role of Base Pairs

17 citations · 29 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG2021★ 2 cited

Highly Efficient Knowledge Graph Embedding Learning with Orthogonal Procrustes Analysis

Xutan Peng, Guanyi Chen, Chenghua Lin +1

Knowledge Graph Embeddings (KGEs) have been intensively explored in recent years due to their promise for a wide range of applications. However, existing studies focus on improving…

cs.IR2021★ 2 cited

UserReg: A Simple but Strong Model for Rating Prediction

Haiyang Zhang, Ivan Ganchev, Nikola S. Nikolov +1

Collaborative filtering (CF) has achieved great success in the field of recommender systems. In recent years, many novel CF models, particularly those based on deep learning or gra…

cs.CL2020★ 17 cited

Robustness and Reliability of Gender Bias Assessment in Word Embeddings: The Role of Base Pairs

Haiyang Zhang, Alison Sneyd, Mark Stevenson

It has been shown that word embeddings can exhibit gender bias, and various methods have been proposed to quantify this. However, the extent to which the methods are capturing soci…

cs.CL2020

Identifying Automatically Generated Headlines using Transformers

Antonis Maronikolakis, Hinrich Schutze, Mark Stevenson

False information spread via the internet and social media influences public opinion and user activity, while generative models enable fake content to be generated faster and more…

cs.IR2020★ 8 cited

Automatic Generation of Topic Labels

Areej Alokaili, Nikolaos Aletras, Mark Stevenson

Topic modelling is a popular unsupervised method for identifying the underlying themes in document collections that has many applications in information retrieval. A topic is usual…