Papers by David Beaver

2 papers
Counterfactual Probing for the Influence of Affect and Specificity on Intergroup Bias (2023.findings-acl)

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Challenge: Existing work on bias in NLP only considers negative or pejorative language use.
Approach: They propose a revised framing of bias in terms of intergroup social context and its effects on language output.
Outcome: The proposed framework is based on a model of intergroup relationships in English language tweets.
Do *they* mean ‘us’? Interpreting Referring Expression variation under Intergroup Bias (2024.findings-emnlp)

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Challenge: We model intergroup bias as a tagging task on English sports comments from forums dedicated to fandom for NFL teams . linguistic descriptions of win probability are used for large-scale analysis of intergroup variation .
Approach: They propose to model intergroup bias as a tagging task on NFL fan comments . they use linguistic models to model the bias and use them to generate large-scale annotations .
Outcome: The proposed model can reveal unobserved variations in the form of referents across win probabilities.

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