Active Learning Helps Pretrained Models Learn the Intended Task

  title={Active Learning Helps Pretrained Models Learn the Intended Task},
  author={Alex Tamkin and Dat Nguyen and Salil Deshpande and Jesse Mu and Noah D. Goodman},
Models can fail in unpredictable ways during deployment due to task ambiguity, when multiple behaviors are consistent with the provided training data. An example is an object classifier trained on red squares and blue circles: when encountering blue squares, the intended behavior is undefined. We investigate whether pretrained models are better active learners, capable of disambiguating between the possible tasks a user may be trying to specify. Intriguingly, we find that better active learning is… 

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