Papers by Chuyan Zhou

1 papers
GiLT: Augmenting Transformer Language Models with Dependency Graphs (2026.acl-long)

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Challenge: Recent work focuses on syntactic tree structures of languages, in particular constituency tree structures.
Approach: They propose a Graph-Infused Layers Transformer Language Model which leverages dependency graphs to augment Transformer language models.
Outcome: The proposed model achieves better syntactic generalization while maintaining competitive perplexity compared with baseline models.

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