300 citations · 660 across the 6 of their papers we have counts for
6 papers
How will advanced AI systems impact democracy?
Christopher Summerfield, Lisa Argyle, Michiel Bakker +20
Advanced AI systems capable of generating humanlike text and multimodal content are now widely available. In this paper, we discuss the impacts that generative artificial intellige…
Collective Constitutional AI: Aligning a Language Model with Public Input
Saffron Huang, Divya Siddarth, Liane Lovitt +4
There is growing consensus that language model (LM) developers should not be the sole deciders of LM behavior, creating a need for methods that enable the broader public to collect…
Generative AI and the Digital Commons
Saffron Huang, Divya Siddarth
Many generative foundation models (or GFMs) are trained on publicly available data and use public infrastructure, but 1) may degrade the "digital commons" that they depend on, and…
Red Teaming Language Models with Language Models
Ethan Perez, Saffron Huang, Francis Song +6
Language Models (LMs) often cannot be deployed because of their potential to harm users in hard-to-predict ways. Prior work identifies harmful behaviors before deployment by using…
Scaling Language Models: Methods, Analysis & Insights from Training Gopher
Jack W. Rae, Sebastian Borgeaud, Trevor Cai +77
Language modelling provides a step towards intelligent communication systems by harnessing large repositories of written human knowledge to better predict and understand the world.…
Improving language models by retrieving from trillions of tokens
Sebastian Borgeaud, Arthur Mensch, Jordan Hoffmann +25
We enhance auto-regressive language models by conditioning on document chunks retrieved from a large corpus, based on local similarity with preceding tokens. With a trillion to…