3 citations · 4 across the 7 of their papers we have counts for
7 papers
Evaluating the Capabilities of LLMs for Persuasive Dialogue
Jordan Robinson, Angus R. Williams, Katie Atkinson +1
Large language models (LLMs) can generate apparently highly persuasive text, but does sounding persuasive mean arguing well? We introduce \textsc{Persuasio}, a multi-agent dialogue…
Validating Political Position Predictions of Arguments
Jordan Robinson, Angus R. Williams, Katie Atkinson +1
Real-world knowledge representation often requires capturing subjective, continuous attributes -- such as political positions -- that conflict with pairwise validation, the widely…
Journalists are most likely to receive abuse: Analysing online abuse of UK public figures across sport, politics, and journalism on Twitter
Liam Burke-Moore, Angus R. Williams, Jonathan Bright
Engaging with online social media platforms is an important part of life as a public figure in modern society, enabling connection with broad audiences and providing a platform for…
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…
Prompto: An open source library for asynchronous querying of LLM endpoints
Ryan Sze-Yin Chan, Federico Nanni, Angus R. Williams +7
Recent surge in Large Language Model (LLM) availability has opened exciting avenues for research. However, efficiently interacting with these models presents a significant hurdle s…
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…
DoDo Learning: DOmain-DemOgraphic Transfer in Language Models for Detecting Abuse Targeted at Public Figures
Angus R. Williams, Hannah Rose Kirk, Liam Burke +6
Public figures receive a disproportionate amount of abuse on social media, impacting their active participation in public life. Automated systems can identify abuse at scale but la…