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--- |
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license: mit |
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pretty_name: ARC bad predictions |
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task_categories: |
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- image-to-image |
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size_categories: |
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- 1K<n<10K |
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language: |
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- en |
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--- |
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# ARC Bad Predictions |
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Visualization of bad predictions: [ARC-AGI training](https://neoneye.github.io/simon-arc-lab-web/model/2024-oct-17-1318/arcagi_training/), [ARC-AGI evaluation](https://neoneye.github.io/simon-arc-lab-web/model/2024-oct-17-1318/arcagi_evaluation/). |
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My goal during the ARC-AGI contests has been to make a `stepwise refinement` algorithm, that can improve on earlier predictions. |
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This repo is intended for `stepwise refinement` algorithms. This dataset contains incorrect predictions that are somewhat close to the target. |
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I have manually inspected these predictions and removed the worst predictions. However there may still be more bad predictions. |
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A bad prediction, can be a hint towards solving the puzzle. |
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A bad prediction, can also be misleading. |
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The color values 0-9 are the same as the ARC-AGI colors. Color values outside this range sometimes occur, when a solver failed to predict that pixel. |
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The `dataset` and `task` correspond to a file found in the [arc-dataset-collection](https://github.com/neoneye/arc-dataset-collection) repo. |
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A few puzzles have multiple versions, these are suffixed with `_v2` and `_v3`. |
