Papers by Desmond Ong

3 papers
Modeling Subjectivity in Cognitive Appraisal with Language Models (2025.findings-emnlp)

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Challenge: a new study explores how language models can quantify subjectivity in cognitive appraisal . existing post-hoc calibration methods fail to achieve satisfactory performance .
Approach: They investigate how language models can quantify subjectivity in cognitive appraisal . existing post-hoc calibration methods often fail to achieve satisfactory performance .
Outcome: The proposed model can quantify subjectivity in cognitive appraisal using fine-tuned models and prompt-based large language models.
Evaluating Subjective Cognitive Appraisals of Emotions from Large Language Models (2023.findings-emnlp)

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Challenge: Existing work on automatic prediction of cognitive appraisals has focused on physiological aspects of emotions.
Approach: They present a dataset that assesses 24 appraisal dimensions across 241 Reddit posts . they find that open-source models fail to automatically assess and explain cognitive appraisals .
Outcome: The proposed dataset assesses 24 appraisal dimensions across 241 reddit posts.
Not All Negatives are Equal: Label-Aware Contrastive Loss for Fine-grained Text Classification (2021.emnlp-main)

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Challenge: Fine-grained classification tasks involve distinguishing between classes with subtle differences between them.
Approach: They analyse fine-grained text classification tasks by embedding class relationships into a contrastive objective function to help differently weigh the positives and negatives.
Outcome: The proposed model outperforms previous contrastive methods on emotion classification and sentiment analysis.

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