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arXiv · 2110.04282

Field Extraction from Forms with Unlabeled Data

Mingfei Gao·Zeyuan Chen·Nikhil Naik·Kazuma Hashimoto·Caiming Xiong·Ran Xu
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Abstract

We propose a novel framework to conduct field extraction from forms with unlabeled data. To bootstrap the training process, we develop a rule-based method for mining noisy pseudo-labels from unlabeled forms. Using the supervisory signal from the pseudo-labels, we extract a discriminative token representation from a transformer-based model by modeling the interaction between text in the form. To prevent the model from overfitting to label noise, we introduce a refinement module based on a progressive pseudo-label ensemble. Experimental results demonstrate the effectiveness of our framework.

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Mingfei Gao, Zeyuan Chen, Nikhil Naik, Kazuma Hashimoto, Caiming Xiong, Ran Xu. 2021-10-08. Field Extraction from Forms with Unlabeled Data. https://arxiv.org/abs/2110.04282

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