Papers by Fenrong Liu

1 papers
Mitigating Spurious Correlations via Counterfactual Contrastive Learning (2025.findings-emnlp)

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Challenge: Existing methods to distinguish causally related words from spurious correlations are limited by the number of causally correlated words in a sentence.
Approach: They propose to use probabilistic probability of necessity and probability of sufficiency to identify causal relationships rather than spurious correlations between words and class labels.
Outcome: The proposed method is based on a contrastive learning approach name CPNS and is validated on public datasets.

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