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Katherine Millican

2 accepted papers

2022

An empirical analysis of compute-optimal large language model training

NeurIPS 2022accept

We investigate the optimal model size and number of tokens for training a transformer language model under a given compute budget. We find that current large language models are significantly undertrained, a consequence of the recent focus on scaling language models whilst keeping the amount of trai…

Cited by 171SourcePDFScholar
2022

Flamingo: a Visual Language Model for Few-Shot Learning

NeurIPS 2022accept

Building models that can be rapidly adapted to novel tasks using only a handful of annotated examples is an open challenge for multimodal machine learning research. We introduce Flamingo, a family of Visual Language Models (VLM) with this ability. We propose key architectural innovations to: (i) bri…

Cited by 4376SourcePDFScholar