Wenbin Luo
Also published as: 文兵 罗
2024
PPDAC: A Plug-and -Play Data Augmentation Component for Few-shot Extractive Question Answering
Qi Huang
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Han Fu
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Wenbin Luo
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Mingwen Wang
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Kaiwei Luo
Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 1: Main Conference)
“Extractive Question Answering (EQA) in the few-shot learning scenario is one of the most chal-lenging tasks of Machine Reading Comprehension (MRC). Some previous works employ exter-nal knowledge for data augmentation to improve the performance of few-shot extractive ques-tion answering. However, there are not always available external knowledge or language- anddomain-specific NLP tools to deal with external knowledge such as part-of-speech taggers, syn-tactic parsers, and named-entity recognizers. In this paper, we present a novel Plug-and-PlayData Augmentation Component (PPDAC) for the few-shot extractive question answering, whichincludes a paraphrase generator and a paraphrase selector. Specifically, we generate multipleparaphrases of the question in the (question, passage, answer) triples using the paraphrase gener-ator and then obtain highly similar statements via paraphrase selector to form more training datafor fine-tuning. Extensive experiments on multiple EQA datasets show that our proposed plug-and-play data augmentation component significantly improves question-answering performance,and consistently outperforms state-of-the-art approaches in few-shot settings by a large margin.”
2023
融合词典信息的古籍命名实体识别研究(A Study on the Recognition of Named Entities of Ancient Books Using Lexical Information)
Wenjun Kang (康文军)
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Jiali Zuo (左家莉)
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Anquan Jie (揭安全)
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Wenbin Luo (罗文兵)
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Mingwen Wang (王明文)
Proceedings of the 22nd Chinese National Conference on Computational Linguistics
“古籍命名实体识别对于古籍实体知识库与语料库的建设具有显著的现实意义。目前古籍命名实体识别的研究较少,主要原因是缺乏足够的训练语料。本文从《资治通鉴》入手,人工构建了一份古籍命名实体识别数据集,以此展开对古籍命名实体识别任务的研究。针对古籍文本多以单字表意且存在大量省略的语言特点,本文采用预训练词向量作为词典信息,充分利用其中蕴涵的词汇信息。实验表明,这种方法可以有效处理古籍文本中人名实体识别的问题。”
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- Mingwen Wang (王明文) 2
- Han Fu 1
- Qi Huang (黄琪) 1
- Anquan Jie (揭安全) 1
- Wenjun Kang (康文军) 1
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