SlowGuess/NeurIPS_2023_OCR huggingface dataset:
(e) CPTPP-M - ML-1M
(f) CPTPP-R - ML-1M
(g) CPTPP-H - Gowalla
(h) CPTPP-M - Gowalla
(i) CPTPP-R - Gowalla
Figure 6: The visualizations of the user embeddings generated by different versions of CPTPP.
B.3 Supplementary Ablation study
The impacts of different personalized prompts on CPTPP are investigated. We visualize the user embeddings produced by all three variations of the proposed CPTPP as shown in Figure 6. We can observe that both CPTPP-H and CPTPP-R have a more uniform distribution, especially on datasets Douban and ML-1M. Such an observation indicates that personalized prompts generated from trainable user profiles can produce user embeddings that have more uniform distributions to demonstrate diverse user preferences better.