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Found 4 papers, 1 papers with code
A LayoutLMv3-Based Model for Enhanced Relation Extraction in Visually-Rich Documents
Document Understanding is an evolving field in Natural Language Processing (NLP).
Information Redundancy and Biases in Public Document Information Extraction Benchmarks
Advances in the Visually-rich Document Understanding (VrDU) field and particularly the Key-Information Extraction (KIE) task are marked with the emergence of efficient Transformer-based approaches such as the LayoutLM models.
Information Extraction from Documents: Question Answering vs Token Classification in real-world setups
Our research showed that when dealing with clean and relatively short entities, it is still best to use token classification-based approach, while the QA approach could be a good alternative for noisy environment or long entities use-cases.
ACNLP at SemEval-2020 Task 6: A Supervised Approach for Definition Extraction
Our systems respectively achieve 0. 830 and 0. 994 F1-scores on the official test set, and we believe that the insights derived from our study are potentially relevant to help advance the research on definition extraction.
