Papers by Peiming Guo
Contrastive Learning on LLM Back Generation Treebank for Cross-domain Constituency Parsing (2025.acl-long)
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| Challenge: | Existing constituency treebanks are limited in out-of-domain settings, therefore constituency parsing is still a challenge. |
| Approach: | They propose a novel method for constituency parsing using large language models . they use a cross-domain constituency treebank to fill missing words with the incomplete one . |
| Outcome: | The proposed method achieves state-of-the-art performance on average compared with baselines on five target domains of MCTB. |
LLM-enhanced Self-training for Cross-domain Constituency Parsing (2023.emnlp-main)
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| Challenge: | Existing approaches to self-training rely on limited and potentially low-quality raw corpora. |
| Approach: | They propose to enhance self-training with the large language model to generate domain-specific raw corpora iteratively and introduce grammar rules that guide the LLM in generating raw corporeals and establish criteria for selecting pseudo instances. |
| Outcome: | The proposed method outperforms traditional methods regardless of the large language model's performance. |