Dear Authors
Thanks for sharing the great work.
For the proposed Clustering-based prompts, I have a few question:
Q1: Step 1: get 1 initial document per question. Wondering why we need to have this step? Seems not benefit to increase diversity?
Q2: Step 2: title said "encoding documents", paragraph said "encode question-document pair"; wondering what do you actually encoding?
Q3: Step 3: Sampling K question-doc paris from K-clusters; How to make sure the document contains relevant information to the question?
Q4: So the intuition of this method is: like in-context learning, providing an "prompt example" for LLM to generate diverse documents; and then giving the sample instruction, the LLM will generate documents with high diversity?
thanks for your attention!
Best,
Dayu
Dear Authors
Thanks for sharing the great work.
For the proposed Clustering-based prompts, I have a few question:
Q1: Step 1: get 1 initial document per question. Wondering why we need to have this step? Seems not benefit to increase diversity?
Q2: Step 2: title said "encoding documents", paragraph said "encode question-document pair"; wondering what do you actually encoding?
Q3: Step 3: Sampling K question-doc paris from K-clusters; How to make sure the document contains relevant information to the question?
Q4: So the intuition of this method is: like in-context learning, providing an "prompt example" for LLM to generate diverse documents; and then giving the sample instruction, the LLM will generate documents with high diversity?
thanks for your attention!
Best,
Dayu