Papers by Minjing Shi

2 papers
Tackling the Root of Misinformation by Teaching Laypeople about Logical Fallacies via Socratic Questioning and Critical Argumentation (2026.acl-long)

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Challenge: Existing systems that detect logical fallacies in public discourse do not help people recognize them independently.
Approach: They propose an intelligent tutoring system which uses large language models to help humans learn about logical fallacies.
Outcome: The proposed system outperforms baseline LLMs lacking such pedagogical strategies.
AFaCTA: Assisting the Annotation of Factual Claim Detection with Reliable LLM Annotators (2024.acl-long)

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Challenge: generative AI is a counter-measure to misinformation, but factual claim detection suffers from inconsistency in definitions and high cost of manual annotation.
Approach: They propose a framework that assists in the annotation of factual claims with the help of large language models.
Outcome: The proposed framework can be used to annotate factual claims with the help of large language models and can work with or without expert supervision.

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