Adaface Sample LLM Questions

You are customizing a Large Language Model (LLM) like GPT-3 to enhance its performance on financial text analysis. To do this, you decide to implement a domain-specific attention mechanism that prioritizes financial terms and concepts during the training process. This mechanism should adjust the attention scores in the model's layers to focus more on tokens related to financial content.
            
            Consider the following simplified pseudocode for a transformer-based LLM where you need to integrate the custom attention mechanism:

In the above pseudocode, you must define the logic for custom_attention to adjust the attention scores effectively. What is the appropriate logic (marked as X) that should be implemented in the custom_attention function to enhance the model's focus on financial tokens?

A: Multiply the scores by a fixed factor if they correspond to domain-specific tokens.
            B: Set scores to zero for tokens not related to the financial domain.
            C: Add a constant value to scores for domain-specific tokens.
            D: Normalize scores based solely on the presence of financial tokens.
            E: Use a softmax function to recalibrate scores based on domain relevance.
            F: Replace scores with pre-defined weights for financial tokens.