Cross-dataset generalization of BaCVA

Investigate and validate the cross-dataset generalization of BaCVA, the Bayesian Context-aware personalized Value Alignment method for inferring context-specific personalized values from static user profiles and scenario-specific value salience.

Background

BaCVA is evaluated primarily on the PRISM and GOOD benchmarks, with additional experiments on AlignX, and is designed to infer personalized value preferences that vary across contextual scenarios. Although the reported experiments demonstrate improvements over baseline methods within the evaluated settings, the extent to which these gains transfer across datasets with different domains, annotation procedures, user populations, and value representations has not been established.

The paper identifies cross-dataset generalization as an unresolved validation requirement. Establishing this generalization would determine whether BaCVA captures transferable contextual personalization patterns rather than exploiting dataset-specific properties.