Sequential Latent Knowledge Selection for Knowledge-Grounded Dialogue
Table 6: Knowledge selection accuracy for each turn on the Wizard of Wikipedia (Dinan et al., 2019). The method with [∗] uses no knowledge loss. TMN stands for E2E Transformer MemNet.
['Method', '[BOLD] Test Seen 1st', '[BOLD] Test Seen 2nd', '[BOLD] Test Seen 3rd', '[BOLD] Test Seen 4th', '[BOLD] Test Seen 5th', '[BOLD] Test Unseen 1st', '[BOLD] Test Unseen 2nd', '[BOLD] Test Unseen 3rd', '[BOLD] Test Unseen 4th', '[BOLD] Test Unseen 5th']
Thanks to the sequential latent variable, our model consistently outperforms other methods for all turns in knowledge selection accuracy. Notably, in all models, the accuracy significantly drops after the first turn, which is often easily predictable as a topic definition sentence.