From Counterfactual Edits to Human Narratives: LLM-Driven Interpretations for Recommender System Explanations
Recommender systems increasingly influence what users discover and consume online, yet the decision logic behind their outputs often remains opaque. Counterfactual explanation (CFX) methods provide an effective way to show which changes to a user's interaction history would alter a recommendation. In recommendation set...