Adversarial Data Insights

Tim discusses the availability and challenges of the Adversarial data set, emphasizing its potential for those interested in argumentation and informal logic. He expresses skepticism about the belief that simply increasing data size will lead to significant improvements in models, highlighting issues like compositional learning and the brittleness of current systems. Tim also suggests innovative approaches to enhance data set preparation, advocating for a balance between linguistic artifacts and labels to create more effective challenges.

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Data Skeptic
BERT is Shallow
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- So there's many people probably preparing some of those data sets. And to your point that we're training to the data sets, not the task, is there anything they can do to, I don't know, make the challenge more effective or go beyond just data set preparation in somewhere? Any advice for people engaged in tasks like that?

Adversarial Data Insights

In this clip

From this podcast

Data Skeptic

BERT is Shallow

Related Questions