Visualizing attention zones in machine reading comprehension models
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Updated: Sep 6, 2025

Eye Tracking During Visually Situated Language Comprehension: Flexibility and Limitations in Uncovering Visual Context Effects
Published on: November 30, 2018
Yiming Cui1, Wei-Nan Zhang2, Ting Liu2
1Research Center for Social Computing and Information Retrieval (SCIR), Harbin Institute of Technology, Harbin 150001, China; State Key Laboratory of Cognitive Intelligence, iFLYTEK Research, Beijing 100083, China.
Abstract:
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. For complete details on the use and execution of this protocol, please refer to Cui et al. (2022).
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