How does embedding pooling improve Generative AI for document similarity tasks

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With the help of code and programming can you tell me How does embedding pooling improve Generative AI for document similarity tasks?
Feb 12 in Generative AI by Ashutosh
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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
answered Feb 12 by ashu

edited Mar 6

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