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@@ -15,4 +15,8 @@ Some data examples are shown below.
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See our [paper](https://github.com/OpenGVLab/all-seeing/all-seeing-v2) to learn more details!
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For a robust evaluation, we adopt CircularEval as our evaluation strategy.
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Under this setting, a question is considered as correctly answered only when the model consistently predicts the correct answer in each of the N iterations, with N corresponding to the number of choices.
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In each iteration, a circular shift is applied to both the choices and the answer to form a new query for the model.
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See our [paper](https://github.com/OpenGVLab/all-seeing/all-seeing-v2) to learn more details!
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