48 citations · 175 across the 29 of their papers we have counts for
8 papers · 1 filter
The Empty Signifier Problem: Towards Clearer Paradigms for Operationalising "Alignment" in Large Language Models
Hannah Rose Kirk, Bertie Vidgen, Paul Röttger +1
In this paper, we address the concept of "alignment" in large language models (LLMs) through the lens of post-structuralist socio-political theory, specifically examining its paral…
SimpleSafetyTests: a Test Suite for Identifying Critical Safety Risks in Large Language Models
Bertie Vidgen, Nino Scherrer, Hannah Rose Kirk +4
The past year has seen rapid acceleration in the development of large language models (LLMs). However, without proper steering and safeguards, LLMs will readily follow malicious in…
The Past, Present and Better Future of Feedback Learning in Large Language Models for Subjective Human Preferences and Values
Hannah Rose Kirk, Andrew M. Bean, Bertie Vidgen +2
Human feedback is increasingly used to steer the behaviours of Large Language Models (LLMs). However, it is unclear how to collect and incorporate feedback in a way that is efficie…
Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow Instructions
Federico Bianchi, Mirac Suzgun, Giuseppe Attanasio +4
Training large language models to follow instructions makes them perform better on a wide range of tasks and generally become more helpful. However, a perfectly helpful model will…
XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language Models
Paul Röttger, Hannah Rose Kirk, Bertie Vidgen +3
Without proper safeguards, large language models will readily follow malicious instructions and generate toxic content. This risk motivates safety efforts such as red-teaming and l…
The Ecological Fallacy in Annotation: Modelling Human Label Variation goes beyond Sociodemographics
Matthias Orlikowski, Paul Röttger, Philipp Cimiano +1
Many NLP tasks exhibit human label variation, where different annotators give different labels to the same texts. This variation is known to depend, at least in part, on the sociod…
Personalisation within bounds: A risk taxonomy and policy framework for the alignment of large language models with personalised feedback
Hannah Rose Kirk, Bertie Vidgen, Paul Röttger +1
Large language models (LLMs) are used to generate content for a wide range of tasks, and are set to reach a growing audience in coming years due to integration in product interface…
SemEval-2023 Task 10: Explainable Detection of Online Sexism
Hannah Rose Kirk, Wenjie Yin, Bertie Vidgen +1
Online sexism is a widespread and harmful phenomenon. Automated tools can assist the detection of sexism at scale. Binary detection, however, disregards the diversity of sexist con…