Papers by Peter Foster

1 papers
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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