Papers with recursive neural networks

3 papers
Recursive Neural Network Based Preordering for English-to-Japanese Machine Translation (P18-3)

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Challenge: Existing methods for preordering require a manual feature design, making language dependent design difficult.
Approach: They propose a preordering method with recursive neural networks that learn features from raw inputs.
Outcome: The proposed method is comparable to the state-of-the-art method but without a manual feature design.
A Real-World Data Resource of Complex Sensitive Sentences Based on Documents from the Monsanto Trial (2020.lrec-1)

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Challenge: Sensitive information detection is of great importance in a number of applications where unintended leaks of sensitive information may incur severe negative consequences.
Approach: They propose to use a corpus of sentences to evaluate sensitive information detection approaches . they employ human annotations and automatically infer labels from domain experts .
Outcome: The proposed models are based on a monsanto trial and are evaluated on sentence level.
Sequential Path Signature Networks for Personalised Longitudinal Language Modeling (2023.findings-acl)

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Challenge: Current work on low-dimensional static user representations or more importantly on dynamic user representation is limited.
Approach: They propose to integrate path signatures from rough path theory into neural sequential models by integrating contextual neural representations and recursive neural networks.
Outcome: The proposed model outperforms state-of-the-art models on macro-average F1 score on two available datasets and outperformed previous models which only have access to historical posts.

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