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arXiv · 2609.37883

Zero-shot Dependency Parsing with Unsupervised Cross-Lingual Bootstrapping

Lalita Lowphansirikul·Attapol Rutherford·Jian Gang Ngui·Sarana Nutanong·Peerat Limkonchotiwat
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Abstract

Pre-trained language models (PLMs) with encoder-based architectures have shown impressive capabilities in zero-shot cross-lingual transfer for various language understanding tasks. However, applying this technique to dependency parsing remains a significant challenge due to its syntactic nature. To boost model generalizability across linguistic typologies, we propose a cross-lingual unsupervised bootstrapping method to improve syntactic knowledge within the PLM. We show that our method achieves a significant improvement in zero-shot parsing performance in low-resource languages. Analysis of these bootstrapped models uncovers increased robustness in recognizing syntactic structures, evidenced by higher scores in parameter-free tree probing tests.

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Lalita Lowphansirikul, Attapol Rutherford, Jian Gang Ngui, Sarana Nutanong, Peerat Limkonchotiwat. 2026-09-29. Zero-shot Dependency Parsing with Unsupervised Cross-Lingual Bootstrapping. https://arxiv.org/abs/2609.37883

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