Papers by Marko Veljanovski

1 papers
DoubleLingo: Causal Estimation with Large Language Models (2024.naacl-short)

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Challenge: Existing methods for causal estimation are inadequate for noisy text data.
Approach: They propose to use LLM-based nuisance models to estimate causal effects from non-randomized data using assumptions about the underlying data distribution.
Outcome: The proposed method reduces the relative absolute error by 10.4% over existing methods on the best available dataset.

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