Exploring Euphemism Detection in Few-Shot and Zero-Shot Settings

Sedrick Scott Keh

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arXiv · 2210.12926

Exploring Euphemism Detection in Few-Shot and Zero-Shot Settings

Sedrick Scott Keh

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Abstract

This work builds upon the Euphemism Detection Shared Task proposed in the EMNLP 2022 FigLang Workshop, and extends it to few-shot and zero-shot settings. We demonstrate a few-shot and zero-shot formulation using the dataset from the shared task, and we conduct experiments in these settings using RoBERTa and GPT-3. Our results show that language models are able to classify euphemistic terms relatively well even on new terms unseen during training, indicating that it is able to capture higher-level concepts related to euphemisms.

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Sedrick Scott Keh. 2022-10-24. Exploring Euphemism Detection in Few-Shot and Zero-Shot Settings. https://arxiv.org/abs/2210.12926

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