Papers by Mark Steyvers

1 papers
Perceptions of Linguistic Uncertainty by Language Models and Humans (2024.emnlp-main)

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Challenge: Prior work has shown that humans are well-attuned to the use of uncertainty expressions, exhibiting population-level agreement in mapping these expressions to numerical responses.
Approach: They propose to map linguistic expressions of uncertainty to numerical responses by using a theory of mind approach to understand the uncertainty of another agent.
Outcome: The proposed model can map expressions to probabilistic responses in a human-like manner, but different behavior depending on whether a statement is actually true or false.

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