Papers by Danilo Silva De Carvalho

1 papers
Learning Disentangled Representations for Natural Language Definitions (2023.findings-eacl)

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Challenge: Disentangling the encodings of neural models is a fundamental aspect for improving interpretability, semantic control and downstream task performance in Natural Language Processing.
Approach: They propose to use syntactic and semantic regularities in textual data to provide models with both structural biases and generative factors.
Outcome: The proposed model outperforms baselines on several qualitative and quantitative benchmarks and improves the results in the downstream task of definition modeling.

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