What does "Discovery Stage" mean?

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The discovery stage is the phase where researchers identify problems or patterns in their study. In this context, it often involves looking closely at how different parts of a model work. For example, when dealing with visual and language models, this stage might focus on finding issues where the model makes mistakes because it relies on misleading connections between images and text.

During this phase, specific features within the images are examined. This helps to pinpoint what is causing errors when the model tries to classify information without prior examples. By using methods that group similar features together, researchers can uncover these misleading connections.

The findings from the discovery stage are crucial because they guide the next steps, allowing researchers to improve the model’s performance and ensure it works better in real-world situations. This careful analysis helps in making models smarter and more reliable in understanding and interpreting data.