Soft Inductive Bias Approach via Explicit Reasoning Perspectives in Inappropriate Utterance Detection Using Large Language Models

This research explores a method for improving inappropriate utterance detection using Large Language Models (LLMs). The approach focuses on incorporating explicit reasoning perspectives and soft inductive biases. The paper likely investigates how to guide LLMs to better identify inappropriate content by providing them with structured reasoning frameworks and potentially incorporating prior knowledge or constraints. The use of "soft inductive bias" suggests a flexible approach that doesn't rigidly constrain the model but rather encourages certain behaviors.