From Dataset Recycling to Multi-Property Extraction and Beyond
Not on the map. Why?
Abstract (arXiv)
This paper investigates various Transformer architectures on the WikiReading Information Extraction and Machine Reading Comprehension dataset. The proposed dual-source model outperforms the current state-of-the-art by a large margin. Next, we introduce WikiReading Recycled-a newly developed public dataset and the task of multiple property extraction. It uses the same data as WikiReading but does not inherit its predecessor's identified disadvantages. In addition, we provide a human-annotated test set with diagnostic subsets for a detailed analysis of model performance.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Nov 2020.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 2; 2022: 1; 2023: 1; 2024: 2.
6 papers.
- 2021Going Full-TILT Boogie on Document Understanding with Text-Image-Layout Transformercited by 134
- 2021Kleister: Key Information Extraction Datasets Involving Long Documents with Complex Layoutscited by 82
- 2022STable: Table Generation Framework for Encoder-Decoder Modelscited by 15
- 2024Notes on Applicability of GPT-4 to Document Understandingcited by 7
- 2023Enabling and Analyzing How to Efficiently Extract Information from Hybrid Long Documents with LLMscited by 2
- 2024Extract Information from Hybrid Long Documents Leveraging LLMs: A Framework and Datasetcited by 0
- 2024Extract Information from Hybrid Long Documents Leveraging LLMs: A Framework and Dataset28 Dec 2024
- 2024Notes on Applicability of GPT-4 to Document Understanding28 May 2024
- 2023Enabling and Analyzing How to Efficiently Extract Information from Hybrid Long Documents with LLMs24 May 2023
- 2022STable: Table Generation Framework for Encoder-Decoder Models8 Jun 2022
- 2021Kleister: Key Information Extraction Datasets Involving Long Documents with Complex Layouts12 May 2021
- 2021Going Full-TILT Boogie on Document Understanding with Text-Image-Layout Transformer18 Feb 2021