4 citations · 11 across the 6 of their papers we have counts for
6 papers
Experiences of Censorship on TikTok Across Marginalised Identities
Eddie L. Ungless, Nina Markl, Björn Ross
TikTok has seen exponential growth as a platform, fuelled by the success of its proprietary recommender algorithm which serves tailored content to every user - though not without c…
Just Because We Camp, Doesn't Mean We Should: The Ethics of Modelling Queer Voices
Atli Sigurgeirsson, Eddie L. Ungless
Modern voice cloning models claim to be able to capture a diverse range of voices. We test the ability of a typical pipeline to capture the style known colloquially as "gay voice"…
Typology of Risks of Generative Text-to-Image Models
Charlotte Bird, Eddie L. Ungless, Atoosa Kasirzadeh
This paper investigates the direct risks and harms associated with modern text-to-image generative models, such as DALL-E and Midjourney, through a comprehensive literature review.…
Stereotypes and Smut: The (Mis)representation of Non-cisgender Identities by Text-to-Image Models
Eddie L. Ungless, Björn Ross, Anne Lauscher
Cutting-edge image generation has been praised for producing high-quality images, suggesting a ubiquitous future in a variety of applications. However, initial studies have pointed…
This Prompt is Measuring <MASK>: Evaluating Bias Evaluation in Language Models
Seraphina Goldfarb-Tarrant, Eddie Ungless, Esma Balkir +1
Bias research in NLP seeks to analyse models for social biases, thus helping NLP practitioners uncover, measure, and mitigate social harms. We analyse the body of work that uses pr…
A Robust Bias Mitigation Procedure Based on the Stereotype Content Model
Eddie L. Ungless, Amy Rafferty, Hrichika Nag +1
The Stereotype Content model (SCM) states that we tend to perceive minority groups as cold, incompetent or both. In this paper we adapt existing work to demonstrate that the Stereo…