Reasoning for Hierarchical Text Classification: The Case of Patents
Reasoning for Hierarchical Classification (RHC) reframes hierarchical text classification as a sequential reasoning task to deduce labels step-by-step. The framework uses a two-stage training process—cold-start alignment with chain-of-thought and reinforcement learning with verifiable rewards—to enable models to predict hierarchical labels from top to bottom while providing human-interpretable justifications.