14.1k citations · 89.2k across the 108 of their papers we have counts for
13 papers · 1 filter
GraphCast: Learning skillful medium-range global weather forecasting
Remi Lam, Alvaro Sanchez-Gonzalez, Matthew Willson +15
Global medium-range weather forecasting is critical to decision-making across many social and economic domains. Traditional numerical weather prediction uses increased compute reso…
Emergent Abilities of Large Language Models
Jason Wei, Yi Tay, Rishi Bommasani +13
Scaling up language models has been shown to predictably improve performance and sample efficiency on a wide range of downstream tasks. This paper instead discusses an unpredictabl…
A Generalist Agent
Scott Reed, Konrad Zolna, Emilio Parisotto +17
Inspired by progress in large-scale language modeling, we apply a similar approach towards building a single generalist agent beyond the realm of text outputs. The agent, which we…
Flamingo: a Visual Language Model for Few-Shot Learning
Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc +24
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 Fl…
Training Compute-Optimal Large Language Models
Jordan Hoffmann, Sebastian Borgeaud, Arthur Mensch +19
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 si…
Non-isotropy Regularization for Proxy-based Deep Metric Learning
Karsten Roth, Oriol Vinyals, Zeynep Akata
Deep Metric Learning (DML) aims to learn representation spaces on which semantic relations can simply be expressed through predefined distance metrics. Best performing approaches c…