Papers with deterministic models
Diversity-aware Event Prediction based on a Conditional Variational Autoencoder with Reconstruction (D19-60)
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| Challenge: | Typical event sequences are important class of commonsense knowledge . previous work in event prediction uses sequence-to-sequence models . however, what can happen after a given event is usually diverse . |
| Approach: | They propose to incorporate a conditional variational autoencoder into seq2seq for its ability to represent diverse next events as a probabilistic distribution. |
| Outcome: | The proposed model outperforms deterministic models in terms of precision and recall . the proposed model is based on a conditional variational autoencoder . |
Contrastive Deterministic Autoencoders For Language Modeling (2023.findings-emnlp)
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| Challenge: | Variational autoencoders (VAEs) are a popular family of generative models with wide applicability. |
| Approach: | They propose to modify a deterministic model designed for images to avoid posterior collapse by controlling the entropy of the aggregate posterior to make it Gaussian. |
| Outcome: | The proposed models outperform a broad range of VAE models on text generation and downstream tasks from representations while avoiding reparametrization steps. |