36 citations · 42 across the 5 of their papers we have counts for
5 papers
Exploring Euphemism Detection in Few-Shot and Zero-Shot Settings
Sedrick Scott Keh
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…
EUREKA: EUphemism Recognition Enhanced through Knn-based methods and Augmentation
Sedrick Scott Keh, Rohit K. Bharadwaj, Emmy Liu +3
We introduce EUREKA, an ensemble-based approach for performing automatic euphemism detection. We (1) identify and correct potentially mislabelled rows in the dataset, (2) curate an…
PINEAPPLE: Personifying INanimate Entities by Acquiring Parallel Personification data for Learning Enhanced generation
Sedrick Scott Keh, Kevin Lu, Varun Gangal +4
A personification is a figure of speech that endows inanimate entities with properties and actions typically seen as requiring animacy. In this paper, we explore the task of person…
Semi-Supervised Noisy Student Pre-training on EfficientNet Architectures for Plant Pathology Classification
Sedrick Scott Keh
In recent years, deep learning has vastly improved the identification and diagnosis of various diseases in plants. In this report, we investigate the problem of pathology classific…
Myers-Briggs Personality Classification and Personality-Specific Language Generation Using Pre-trained Language Models
Sedrick Scott Keh, I-Tsun Cheng
The Myers-Briggs Type Indicator (MBTI) is a popular personality metric that uses four dichotomies as indicators of personality traits. This paper examines the use of pre-trained la…