Value Retrieval with Arbitrary Queries for Form-like Documents

Gao, Mingfei, Xue, Le, Ramaiah, Chetan, Xing, Chen, Xu, Ran, Xiong, Caiming

arXiv.org Artificial Intelligence 

We propose value retrieval with arbitrary queries for form-like documents to reduce human effort of processing forms. Unlike previous methods that only address a fixed set of field items, our method predicts target value for an arbitrary query based on the understanding of layout and semantics of a form. To further boost model performance, we propose a simple document language modeling (simpleDLM) strategy to improve document understanding on large-scale model pre-training. Experimental results show that our method outperforms our baselines significantly and the simpleDLM further improves our performance on value retrieval by around 17\% F1 score compared with the state-of-the-art pre-training method. Code will be made publicly available.