Recent research in explainable recommendation commonly uses natural language explanations to improve transparency and user trust. However, reliably evaluating whether explanations are semantically faithful to users’ multi-dimensional preferences remains challenging. Existing methods mainly rely on text similarity metri...
Chen-Fu Yu, Qing-Lin Huang, Xiao-Xuan Shen et al.· Proceedings of the 20th ACM...· 0 citations
Recent research in explainable recommendation commonly uses natural language explanations to improve transparency and user trust. However, reliably evaluating whether explanations are semantically faithful to users’ multi-dimensional preferences remains challenging. Existing methods mainly rely on text similarity metri...
Chen-Fu Yu, Qing-Lin Huang, Xiao-Xuan Shen et al.· Proceedings of the 20th ACM...· 0 citations
Situational judgment tests (SJTs) are a well-established class of assessment instruments that embed measurement within realistic scenarios, eliciting context-driven responses that are less susceptible to social desirability bias and more effective at capturing applied judgment than traditional self-report scales. Despi...
Jian-Wen Sun, Fucheng Guo, Zongkai Yang et al.· IEEE Transactions on Learnin...· 0 citations
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