66 citations · 104 across the 9 of their papers we have counts for
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cs.LG2023★ 1 cited
SequenceMatch: Imitation Learning for Autoregressive Sequence Modelling with Backtracking
Chris Cundy, Stefano Ermon
In many domains, autoregressive models can attain high likelihood on the task of predicting the next observation. However, this maximum-likelihood (MLE) objective does not necessar…
cs.AI2023★ 66 cited
On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligence
Gengchen Mai, Weiming Huang, Jin Sun +11
Large pre-trained models, also known as foundation models (FMs), are trained in a task-agnostic manner on large-scale data and can be adapted to a wide range of downstream tasks by…