How does inverse attention masking optimize Generative AI for ambiguity resolution

Question

With the hep of proper code and examples can you tell me How does inverse attention masking optimize Generative AI for ambiguity resolution?

Answer 1

Inverse attention masking optimizes Generative AI for ambiguity resolution by suppressing irrelevant context while enhancing critical information.

Here is the code snippet you can refer to:

In the above code we are using the following key points:

• Ambiguity Suppression: Reduces the influence of misleading tokens.
• Context Refinement: Focuses on disambiguating elements in a sequence.
• Dynamic Adaptation: Adjusts attention weights based on learned patterns.
• Improved Precision: Enhances decision-making in generative models.

Hence, by referring to above, you can optimize Generative AI for ambiguity resolution