Papers by Victor Veitch

2 papers
Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond (2022.tacl-1)

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Challenge: causality has not had the same importance in natural language processing, says aaron e. smith . he says research on causality in NLP remains scattered across domains without unified definitions .
Approach: They propose to consolidate research on causality in NLP across academic areas . they explore potential uses of causal inference to improve robustness, fairness, interpretability .
Outcome: The proposed method is a unified overview of causal inference for the NLP community.
Causal Effects of Linguistic Properties (2021.naacl-main)

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Challenge: Social scientists have long been interested in the causal effects of language, studying questions like: How should political candidates describe their personal history to appeal to voters?
Approach: They propose an algorithm for estimating causal effects of linguistic properties that leverages distant supervision and a pre-trained language model to adjust for the text.
Outcome: The proposed method outperforms other methods when estimating the effect of Amazon review sentiment on semi-simulated sales figures.

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