Papers by Hao Xve

1 papers
A Systematic Study of Compositional Syntactic Transformer Language Models (2025.acl-long)

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Challenge: Syntactic language models (SLMs) incorporate syntactical biases into Transformers . authors identify key aspects of design choices in existing models and novel variants based on experimental results .
Approach: They propose a framework that incorporates existing and new SLMs to enhance Transformers by incorporating syntactic biases.
Outcome: The proposed framework improves on existing models and novel variants across language modeling, syntactic generalization, summarization, and inference efficiency.

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