Papers with Dirichlet distribution

2 papers
Dirichlet Latent Variable Hierarchical Recurrent Encoder-Decoder in Dialogue Generation (D19-1)

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Challenge: Existing work assumes the Gaussian priors of the latent variable, which are incapable of representing complex latent variables effectively.
Approach: They propose to use the Dirichlet distribution with flexible structures to characterize latent variables in place of the Gaussian priors.
Outcome: The proposed model outperforms existing models on the dialogue generation task.
TimeTraveler: Reinforcement Learning for Temporal Knowledge Graph Forecasting (2021.emnlp-main)

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Challenge: Existing methods focus on reasoning at past timestamps to complete the missing facts, and there are only a few works of reasoning on known TKGs to forecast future facts.
Approach: They propose a time-shaped reward method that captures historical knowledge graph snapshots and a new representation method for unseen entities to improve the inductive inference ability of the model.
Outcome: The proposed method improves on four benchmark datasets with higher explainability, less calculation, and fewer parameters when compared with existing state-of-the-art methods.

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