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20192024
most citedScaling Language Models: Methods, Analysis & Insights from Training Gopher

243 citations · 495 across the 7 of their papers we have counts for

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Showing cs.CLShow all

5 papers · 1 filter

cs.CL2022★ 12 cited

Characteristics of Harmful Text: Towards Rigorous Benchmarking of Language Models

Maribeth Rauh, John Mellor, Jonathan Uesato +9

Large language models produce human-like text that drive a growing number of applications. However, recent literature and, increasingly, real world observations, have demonstrated…

cs.CL2022★ 243 cited

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.…

cs.CL2021★ 71 cited

Ethical and social risks of harm from Language Models

Laura Weidinger, John Mellor, Maribeth Rauh +20

This paper aims to help structure the risk landscape associated with large-scale Language Models (LMs). In order to foster advances in responsible innovation, an in-depth understan…

cs.CL2021

Challenges in Detoxifying Language Models

Johannes Welbl, Amelia Glaese, Jonathan Uesato +7

Large language models (LM) generate remarkably fluent text and can be efficiently adapted across NLP tasks. Measuring and guaranteeing the quality of generated text in terms of saf…

cs.CL2021★ 12 cited

Decoupling the Role of Data, Attention, and Losses in Multimodal Transformers

Lisa Anne Hendricks, John Mellor, Rosalia Schneider +2

Recently multimodal transformer models have gained popularity because their performance on language and vision tasks suggest they learn rich visual-linguistic representations. Focu…