mlsanityData to 7 Oct 2026

Jointly Learning Span Extraction and Sequence Labeling for Information Extraction from Business Documents

arXiv 2205.13434 ↗First posted 26 May 2022cs.CL cs.AIcited by 4

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Abstract (arXiv)

This paper introduces a new information extraction model for business documents. Different from prior studies which only base on span extraction or sequence labeling, the model takes into account advantage of both span extraction and sequence labeling. The combination allows the model to deal with long documents with sparse information (the small amount of extracted information). The model is trained end-to-end to jointly optimize the two tasks in a unified manner. Experimental results on four business datasets in English and Japanese show that the model achieves promising results and is significantly faster than the normal span-based extraction method. The code is also available.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 18 of its 32 references that are in the map. First posted on arXiv 26 May 2022.

Builds on

18 of 32 references.

References · 18

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  2. 2019DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lightercited by 4,243
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  12. 2021Few-Shot Question Answering by Pretraining Span Selectioncited by 62
6 more
  1. 2021A Span-Based Model for Joint Overlapped and Discontinuous Named Entity Recognitioncited by 33
  2. 2020TXtract: Taxonomy-Aware Knowledge Extraction for Thousands of Product Categoriescited by 29
  3. 2017Empower Sequence Labeling with Task-Aware Neural Language Modelcited by 28
  4. 2020Nested Named Entity Recognition with Partially-Observed TreeCRFscited by 23
  5. 2020Rapid Adaptation of BERT for Information Extraction on Domain-Specific Business Documentscited by 8
  6. 2021A Span Extraction Approach for Information Extraction on Visually-Rich Documentscited by 6

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Cited by year

Citing papers per year: 2022: 1; 2023: 1; 2024: 1; 2025: 1.

4 papers.

  1. 2024Scoping Review of Active Learning Strategies and their Evaluation Environments for Entity Recognition Taskscited by 2
  2. 2023Towards Safer Operations: An Expert-involved Dataset of High-Pressure Gas Incidents for Preventing Future Failurescited by 1
  3. 2022Improving Document Image Understanding with Reinforcement Finetuningcited by 0
  4. 2025CareLab at #SMM4H-HeaRD 2025: Insomnia Detection and Food Safety Event Extraction with Domain-Aware Transformerscited by 0