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Generative answers citations duplicated

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Posted on by Giacamic

Hello,

When getting a response from conversational boosting topic (generative answer) with a SharePoint data source, the citations/links in responses are duplicated multiple times.

1,2,3 are all the same link. I believe typically a number would be tied to a unique reference in citations like this, so it is a bit confusing for users.

Does anyone know why this occurs or if there is a way to modify this behavior?

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mboninco Microsoft Employee on at

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@Giacamic Thanks for the feedback.

This normally occurs when the response is coming from different sections of the same reference. I'll pass this on to those working on improving the citations.

-- Mike Bonincontri

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Hammadopt 5 on at

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any update on this?

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Giacamic 23 on at

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I am still having the same behavior as above. As well as citations occasionally pointing to irrelevant documents or documents cited in previous questions.

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Hammadopt 5 on at

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I have tried the following solutions without any luck:
Changed the assistant prompt to make sure it is not showing duplicates.
Used the “Custom instructions (preview)” feature to give instructions to GPT response.
Tried showing customized answers without using GPT, this may work but summarization by GPT is required.
Used another step for “Create generative answers” with custom data as JSON array from the previous step and gave input as prompt to show summary and without duplicate references.

@mboninco - do you if this is a known issue? or may be there is a way to fix.

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citron-truc 394 on at

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Hello !

When you ask for a generative answer, this is what happens :
- The copilot takes every document in the sharepoint and cuts them into chunks that are small enough to be treated in one go by the GPT model.
- The chunks are ranked according to their relevance to the question.
- There is a hidden prompt where you ask the GPT model "with these five most relevant documents, could you answer this user question ?"
- The GPT returns an answer with links pointing to the documents whose chunks were used.

At no moment does the model check if there are duplicates (and therefore they are bound to happen unfortunately 🥲)

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