Papers by Christiane Fellbaum

2 papers
A Corpus-based Syntactic Analysis of Two-termed Unlike Coordination (2021.findings-emnlp)

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Challenge: a phenomenon of language that conjoins two or more terms or phrases using a coordinating conjunction is still largely elusive and widely debated amongst linguists.
Approach: They propose to use a computational corpus-based approach to study two-termed unlike coordinations where the two conjuncts of the coordination phrase form valid constituents but have distinct categories.
Outcome: The proposed analysis shows that the two conjuncts within unlike coordinations display different properties based on their position, supporting an antisymmetric view of the structure of coordination.
MABEL: Attenuating Gender Bias using Textual Entailment Data (2022.emnlp-main)

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Challenge: Existing methods for mitigating gender bias in language models are insufficient or inconsistent.
Approach: They propose a method for attenuating gender bias using entailment labels . they use a contrastive learning objective on counterfactually augmented enanglement pairs .
Outcome: The proposed method outperforms previous task-agnostic debiasing approaches on intrinsic and extrinsic metrics and preserves task performance after fine-tuning on downstream tasks.

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