Graph neural networks are increasingly used to make predictions on relational data in settings such as social and financial networks. Yet, assessing whether these models treat demographic groups comparably is difficult because bias can arise not only from node attributes but also from the graph structure that drives message passing. By introducing a model-agnostic visual …
Day: December 19, 2025
A Comparative Analysis of Text-Based Explainable Recommender Systems
We reproduce and benchmark prominent text-based explainable recommender systems to test the recurring claim that hybrid retrieval-augmented approaches deliver the best overall balance between explanation quality and grounding. Yet, prior evidence is hard to compare because studies diverge in datasets, preprocessing, target explanation definitions, baselines, and evaluation metrics. Under a unified benchmark on three real-world …