Ruyuan Wan — accepted AI-conference papers

2024

CoCoLoFa: A Dataset of News Comments with Common Logical Fallacies Written by LLM-Assisted Crowds

Min-Hsuan Yeh, Ruyuan Wan, Ting-Hao Kenneth Huang

EMNLP 2024main

Detecting logical fallacies in texts can help users spot argument flaws, but automating this detection is not easy. Manually annotating fallacies in large-scale, real-world text data to create datasets for developing and validating detection models is costly. This paper introduces CoCoLoFa, the larg…

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2023

Everyone’s Voice Matters: Quantifying Annotation Disagreement Using Demographic Information

Ruyuan Wan, Jaehyung Kim, Dongyeop Kang

AAAI 2023technical

In NLP annotation, it is common to have multiple annotators label the text and then obtain the ground truth labels based on major annotators’ agreement. However, annotators are individuals with different backgrounds and various voices. When annotation tasks become subjective, such as detecting polit…

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