activity
20192024
most citedTowards an Enhanced Understanding of Bias in Pre-trained Neural Language Models: A Survey with Special Emphasis on Affective Bias

13 citations · 41 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CY2024

On the Political Economy of Link-based Web Search

Deepak P, James Steinhoff, Stanley Simoes

Web search engines arguably form the most popular data-driven systems in contemporary society. They wield a considerable power by functioning as gatekeepers of the Web, with most u…

cs.CY2023

AI and Core Electoral Processes: Mapping the Horizons

Deepak P, Stanley Simoes, Muiris MacCarthaigh

Significant enthusiasm around AI uptake has been witnessed across societies globally. The electoral process -- the time, place and manner of elections within democratic nations --…

cs.CL2023★ 2 cited

REDAffectiveLM: Leveraging Affect Enriched Embedding and Transformer-based Neural Language Model for Readers' Emotion Detection

Anoop Kadan, Deepak P., Manjary P. Gangan +2

Technological advancements in web platforms allow people to express and share emotions towards textual write-ups written and shared by others. This brings about different interesti…

cs.LG2022★ 1 cited

Cluster-level Group Representativity Fairness in -means Clustering

Stanley Simoes, Deepak P, Muiris MacCarthaigh

There has been much interest recently in developing fair clustering algorithms that seek to do justice to the representation of groups defined along sensitive attributes such as ra…

cs.CL2022★ 7 cited

Why are NLP Models Fumbling at Elementary Math? A Survey of Deep Learning based Word Problem Solvers

Sowmya S Sundaram, Sairam Gurajada, Marco Fisichella +2

From the latter half of the last decade, there has been a growing interest in developing algorithms for automatically solving mathematical word problems (MWP). It is a challenging…

cs.LG2022

Exploring Rawlsian Fairness for K-Means Clustering

Stanley Simoes, Deepak P, Muiris MacCarthaigh

We conduct an exploratory study that looks at incorporating John Rawls' ideas on fairness into existing unsupervised machine learning algorithms. Our focus is on the task of cluste…