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Conversational Response Re ranking Based on Event Causality and Role Factored Tensor Event Embedding

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Academic year: 2020

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Figure

Figure 1: Neural conversational model+re-ranking using event causality; a response that has an event causalityrelation (“be exhausted” → “relax”) to the dialogue history is selected by the re-ranking.
Figure 2: Model architecture of predicate embedding
Table 3: Comparison results before and after re-ranking
Table 4: 1-best v.s. Re-ranking; # dialogues is 100.

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