Thank you for your response! That clears things up a bit.
So in essence what you are proposing is modifying the Transformer architecture for processing emotional valuation alongside semantic meanings. Both start out as per-token embeddings, and are then updated via their respective attention mechanisms and NLP layers.
I’m not sure if I have the whole picture, or even if what I wrote above is a correct model of your proposal. I think my biggest confusion is this:
Are the semantic and emotional information flows fully parallel, or do they update each other along the way?
While semantic and emotional information flows start in parallel, they are not fully parallel throughout the entire process. They update each other iteratively, enabling it to capture intricate connections between semantic content and emotional tone. This has the potential to enhance the model’s comprehension of the input text, resulting in a more refined understanding.
Thank you for your response! That clears things up a bit.
So in essence what you are proposing is modifying the Transformer architecture for processing emotional valuation alongside semantic meanings. Both start out as per-token embeddings, and are then updated via their respective attention mechanisms and NLP layers.
I’m not sure if I have the whole picture, or even if what I wrote above is a correct model of your proposal. I think my biggest confusion is this:
Are the semantic and emotional information flows fully parallel, or do they update each other along the way?
While semantic and emotional information flows start in parallel, they are not fully parallel throughout the entire process. They update each other iteratively, enabling it to capture intricate connections between semantic content and emotional tone. This has the potential to enhance the model’s comprehension of the input text, resulting in a more refined understanding.