基于数据选择和局部伪标注的跨语义依存分析研究(Selection and Pseudo Partial Annotationy)

CCL 2021  ·  Dazhan Mao, Kuai Yu, Yanqiu Shao ·

“语义依存分析要走向实用,模型从单领域迁移到其他领域的领域适应能力至关重要。近年来,对抗学习针对领域适应这个任务取得了较好的效果,但对目标领域的无标注数据利用效率并不高。本文采用Self-training这种半监督学习方法,充分发挥无标注数据的潜能,弥补对抗学习方法的不足。但传统的Self-training效率和性能并不好,为此本文针对跨领域语义依存分析这个任务,尝试了强化学习数据选择器,提出了局部伪标注的标注策略,实验结果证明我们提出的模型优于基线模型。”

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