Papers with Hierarchical Dirichlet Process-Spectral Mixture Latent Dirichlet Allocation

1 papers
Learning Adverbs with Spectral Mixture Kernels (2024.findings-acl)

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Challenge: In order for robots to collaborate with humans, it is important to share and understand their experiences through language.
Approach: They propose a hierarchical Dirichlet Process-Spectral Mixture Latent Dirichlets Allocation model which learns the relationship between human motions and adverbs by capturing frequency kernels that represent motion characteristics and shared topics of a given aadverts.
Outcome: The proposed model outperforms representative neural network models in terms of perplexity score and predicts more appropriate adverbs.

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