How does embedding pooling improve Generative AI for document similarity tasks

Question

With the help of code and programming can you tell me How does embedding pooling improve Generative AI for document similarity tasks?

Answer 1

Embedding pooling improves Generative AI for document similarity tasks by aggregating token-level embeddings into a fixed-size vector, making comparisons efficient and robust.

Here is the code snippet you can refer to:

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

• Dimensionality Reduction: Converts variable-length text into a fixed-size vector.
• Improved Similarity Computation: Enables efficient cosine similarity or distance-based comparisons.
• Robustness: Reduces noise and captures essential semantic meaning.
• Scalability: Efficiently processes large-scale document sets.

Hence, by referring to the above, you can improve Generative AI for document similarity tasks