Papers by Christos Papadimitriou

1 papers
Self-Attention Networks Can Process Bounded Hierarchical Languages (2021.acl-long)

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Challenge: Existing models that can process formal languages with hierarchical structure are limited in their performance.
Approach: They propose to use a subset of Dyck-k with depth bounded by D to train self-attention networks.
Outcome: The proposed model can process Dyck-(k, D) with depth bounded by D, which better captures the hierarchical structure of natural language.

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