What does "EAP" mean?
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EAP stands for Edge Attribution Patching. It is a method used to study how language models work by looking at the connections between different parts of the model. This approach helps researchers understand which parts of the model are important for making decisions.
How Does EAP Work?
EAP involves changing or removing connections in the model to see how it affects performance. This lets researchers figure out which connections are necessary for the model to work well on a task. However, this method has limitations, especially as models get larger.
The Need for Improvement
Since traditional methods can be slow and difficult to apply to big models, EAP was introduced as a quicker way to get insights. Even though it works better than earlier methods, it doesn't always provide complete accuracy.
EAP with Integrated Gradients
A newer method called EAP with Integrated Gradients aims to improve on the regular EAP by making sure that the findings are more reliable. This method focuses on maintaining what is called "faithfulness," which means that if you remove other connections outside of the core ones, the model's performance won't change.
Conclusion
EAP and its improvement help researchers better understand how language models operate, leading to more reliable insights into their mechanisms.