Papers by Kaixin Zheng

2 papers
Simplified Graph Learning for Inductive Short Text Classification (2022.emnlp-main)

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Challenge: Existing methods for short text classification are limited and lack of labeled data is not enough.
Approach: They propose a novel short text classification algorithm which leverages words to handle the lack of labeled data.
Outcome: The proposed model performs better with lower memory consumption and faster inference speed than previous models.
Beyond Boundaries: Learning a Universal Entity Taxonomy across Datasets and Languages for Open Named Entity Recognition (2025.coling-main)

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Challenge: Current Large Language Models struggle with complex entity taxonomies in open domains and lack NER capabilities.
Approach: They propose a dataset to guide LLMs' generalization in Open NER under a universal entity taxonomy.
Outcome: The proposed model outperforms GPT-4 in 3 out-of-domain benchmarks across 15 datasets and 6 languages.

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