Chengyu Wang

KEML: A Knowledge-Enriched Meta-Learning Framework for Lexical Relation Classification

2020 · arXiv (Cornell University)

Lexical relations describe how concepts are semantically related, in the form of relation triples. The accurate prediction of lexical relations between concepts is challenging, due to the sparsity of patterns indicating the existence of such …

TransPrompt v2: Transferable Prompt-based Fine-tuning for Few-shot Text Classification

2022 · Research Square

Abstract Recent studies have shown that prompt-based fine-tuning improves the performance of large Pre-trained Language Models (PLMs) for few-shot text classification. Specifically, this type of method transforms the text classification task into the inherent Masked …

Hierarchical Label-Enhanced Contrastive Learning for Chinese NER

2025 · IEEE Transactions on Neural Networks and Learning Systems

Recently, character-word lattice structures have achieved promising results for Chinese named entity recognition (NER), reducing word segmentation errors and increasing word boundary information for character sequences. However, constructing the lattice structure is complex and time-consuming, …