Papers by Geonyeong Son

2 papers
ESG-Kor: A Korean Dataset for ESG-related Information Extraction and Practical Use Cases (2024.findings-emnlp)

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Challenge: Pre-trained language models are exhibiting astonishing performances in various natural language processing tasks, including classification, question answering, machine translation, summarization, and conversation generation.
Approach: They built a Korean dataset to automatically extract Environmental, Social, and Governance (ESG) information from Korean companies’ sustainability reports and manually labeled it according to objective rules provided by ESG evaluation agencies.
Outcome: The proposed dataset extracts environmental, social, and governance information from Korean companies’ sustainability reports and labels it according to objective rules provided by ESG evaluation agencies.
From Curiosity to Clarity : Exploring the Impact of Consecutive Why-Questions (2025.findings-naacl)

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Challenge: a recent study has demonstrated the utility of consecutive why-questions in everyday life.
Approach: They used a WHY-Chain dataset to construct a model that asked a why-questions question . they also used objectives that capture the 'consecutive' characteristic of the data .
Outcome: The proposed model performed better on downstream tasks that require commonsense reasoning . the model was validated by ablation studies and the validity check .

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