Web: http://arxiv.org/abs/2208.11508

Sept. 16, 2022, 1:16 a.m. | Guanting Dong, Daichi Guo, Liwen Wang, Xuefeng Li, Zechen Wang, Chen Zeng, Keqing He, Jinzheng Zhao, Hao Lei, Xinyue Cui, Yi Huang, Junlan Feng, Weira

cs.CL updates on arXiv.org arxiv.org

Most existing slot filling models tend to memorize inherent patterns of
entities and corresponding contexts from training data. However, these models
can lead to system failure or undesirable outputs when being exposed to spoken
language perturbation or variation in practice. We propose a perturbed semantic
structure awareness transferring method for training perturbation-robust slot
filling models. Specifically, we introduce two MLM-based training strategies to
respectively learn contextual semantic structure and word distribution from
unsupervised language perturbation corpus. Then, we transfer semantic …

arxiv semantic

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