Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond

Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond

AbstractA fundamental goal of scientific research is to learn about causal relationships. However, despite its critical role in the life and social sciences, causality has not had the same importance in Natural Language Processing (NLP), which has traditionally placed more emphasis o...

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Bibliographic Details
Main Authors: Amir Feder, Katherine A. Keith, Emaad Manzoor, Reid Pryzant, Dhanya Sridhar, Zach Wood-Doughty, Jacob Eisenstein, Justin Grimmer, Roi Reichart, Margaret E. Roberts, Brandon M. Stewart, Victor Veitch, Diyi Yang
Format: Article
Language:English
Published: The MIT Press 2022-01-01
Series:Transactions of the Association for Computational Linguistics
Online Access:https://direct.mit.edu/tacl/article/doi/10.1162/tacl_a_00511/113490/Causal-Inference-in-Natural-Language-Processing

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https://direct.mit.edu/tacl/article/doi/10.1162/tacl_a_00511/113490/Causal-Inference-in-Natural-Language-Processing

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