Hongli Mao — accepted AI-conference papers

2024

Span Graph Transformer for Document-Level Named Entity Recognition

Hongli Mao, Xian-Ling Mao, Hanlin Tang, Yu-Ming Shang, Heyan Huang

AAAI 2024technical

Named Entity Recognition (NER), which aims to identify the span and category of entities within text, is a fundamental task in natural language processing. Recent NER approaches have featured pre-trained transformer-based models (e.g., BERT) as a crucial encoding component to achieve state-of-the…

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2024

Span-based Unified Named Entity Recognition Framework via Contrastive Learning

Hongli Mao, Xian-Ling Mao, Hanlin Tang, Yu-Ming Shang, Xiaoyan Gao, Ao-Jie Ma +1

IJCAI 2024poster

Traditional Named Entity Recognition (NER) models are typically designed for domain-specific datasets and limited to fixed predefined types, resulting in difficulty generalizing to new domains. Recently, prompt-based generative methods attempt to mitigate this constraint by training models jointly…

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