4 papers
The Heterogeneous Safety Impacts of Benign Multilingual Fine-Tuning
Will Hawkins, Kaivalya Rawal, Jonathan Rystrøm +8
Fine-tuning a large language model is a ubiquitous method for enhancing its capability on a specific downstream task. However, prior work has shown that this increase in capability…
Evaluating Language Models for Harmful Manipulation
Canfer Akbulut, Rasmi Elasmar, Abhishek Roy +9
Interest in the concept of AI-driven harmful manipulation is growing, yet current approaches to evaluating it are limited. This paper introduces a framework for evaluating harmful…
Deepfakes on Demand: the rise of accessible non-consensual deepfake image generators
Will Hawkins, Chris Russell, Brent Mittelstadt
Advances in multimodal machine learning have made text-to-image (T2I) models increasingly accessible and popular. However, T2I models introduce risks such as the generation of non-…
The effect of fine-tuning on language model toxicity
Will Hawkins, Brent Mittelstadt, Chris Russell
Fine-tuning language models has become increasingly popular following the proliferation of open models and improvements in cost-effective parameter efficient fine-tuning. However,…