8 citations · 10 across the 9 of their papers we have counts for
4 papers · 1 filter
Large language models can consistently generate high-quality content for election disinformation operations
Angus R. Williams, Liam Burke-Moore, Ryan Sze-Yin Chan +7
Advances in large language models have raised concerns about their potential use in generating compelling election disinformation at scale. This study presents a two-part investiga…
NLP for Counterspeech against Hate: A Survey and How-To Guide
Helena Bonaldi, Yi-Ling Chung, Gavin Abercrombie +1
In recent years, counterspeech has emerged as one of the most promising strategies to fight online hate. These non-escalatory responses tackle online abuse while preserving the fre…
Basque and Spanish Counter Narrative Generation: Data Creation and Evaluation
Jaione Bengoetxea, Yi-Ling Chung, Marco Guerini +1
Counter Narratives (CNs) are non-negative textual responses to Hate Speech (HS) aiming at defusing online hatred and mitigating its spreading across media. Despite the recent incre…
Cheap Learning: Maximising Performance of Language Models for Social Data Science Using Minimal Data
Leonardo Castro-Gonzalez, Yi-Ling Chung, Hannak Rose Kirk +4
The field of machine learning has recently made significant progress in reducing the requirements for labelled training data when building new models. These `cheaper' learning tech…