The attention transition module is trained and validated under different tasks. Average performance of 7-fold cross validation is reported.

-   **AT\_s**: The attention transition module is trained and validated on two splits of the same task. Average performance of 7 tasks is reported.

-   **SP+AT\_d**: The late fusion on top of **SP** and **AT\_d**.

-   **SP+AT\_s**: The late fusion on top of **SP** and **AT\_s**.

![AUC and AAE scores of cross task validation. Five different experiment settings (explained in the text below) are compared to study the differences of attention transition in different tasks. []{data-label="fig:crosstask"}](Ablationfig4.pdf){width="0.9\linewidth"}

Quantitative results of different settings are shown in Figure \[fig:crosstask\]. Both AUC and AAE scores show the same performance trend with different settings. AT\_d works worse than SP, while AT\_s outperforms SP. This is probably due to the differences of gaze behavior contained in different tasks. However, SP+AT\_d with the late fusion module can still improve the performance compared with SP and AT\_s, even with the context learned from different tasks.

Examination of the attention transition module {#Experiment:AA}
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We further demonstrate that our attention transition module is able to learn meaningful transition between adjacent gaze fixations. This ability has important applications in computer-aided AR 