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Found 3 papers, 1 papers with code
Autoformalizing Natural Language to First-Order Logic: A Case Study in Logical Fallacy Detection
In this paper, we introduce Natural Language to First-Order Logic (NL2FOL), a framework to autoformalize natural language to FOL step by step using Large Language Models (LLMs).
Machine Learning in Sports: A Case Study on Using Explainable Models for Predicting Outcomes of Volleyball Matches
Therefore, it is required to provide high-quality interpretable, and understandable explanations for a model's prediction in sports.
Decision Making
Explainable Artificial Intelligence (XAI)
+2
Logical Fallacy Detection
In this paper, we propose the task of logical fallacy detection, and provide a new dataset (Logic) of logical fallacies generally found in text, together with an additional challenge set for detecting logical fallacies in climate change claims (LogicClimate).
