Visualizing attention zones in machine reading comprehension models
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Abstract (arXiv)
The attention mechanism plays an important role in the machine reading comprehension (MRC) model. Here, we describe a pipeline for building an MRC model with a pretrained language model and visualizing the effect of each attention zone in different layers, which can indicate the explainability of the model. With the presented protocol and accompanying code, researchers can easily visualize the relevance of each attention zone in the MRC model. This approach can be generalized to other pretrained language models.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 7 of its 16 references that are in the map. First posted on arXiv 28 Oct 2024.
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References · 7
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- 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
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- 2016SQuAD: 100,000+ Questions for Machine Comprehension of Textcited by 4,115
- 2018A Span-Extraction Dataset for Chinese Machine Reading Comprehensioncited by 84
- 2021Multilingual Multi-Aspect Explainability Analyses on Machine Reading Comprehension Modelscited by 5
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