US 2026/0300623 A1Published application

Copy suppression for retrieval-augmented generation outputs

AssigneeAmazon Technologies, Inc.

InventorsAws Albarghouthi, Tancrede Lepoint

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Abstract

Described are systems and processes for providing copy protection in results provided by a Large Language Model (LLM) that uses Retrieval-Augmented Generation (RAG) of data sources. The data sources may be sharded into a first shard and a second shard. A first query may be sent to the LLM using RAG with the first shard to determine a token with a first probability. A second query may be sent to the LLM using RAG with the second shard to determine the token with a second probability. A combined probability may be determined for the token based on the first probability and the second probability. The combined probability may be used to select the token. These systems and processes reduce a risk that the LLM is too closely tied to any specific data and thus replicates an extended amount of that data.

Claims20

Dependent claims

A system, comprising:

one or more processors;
and
memory storing program instructions that, when executed by the one or more processors, cause the one or more processors to at least:
determine that a data source includes sensitive data;
shard the data source into at least a first shard and a second shard;
receive a request for generative text to be provided in part by a large language model (LLM) implemented with retrieval-augmented generation (RAG) and having access to at least the first shard and the second shard;
send a first query to the LLM implementing the RAG with the first shard to obtain first probabilities associated with first tokens used to determine a next token in the generative text;
send a second query to the LLM implementing the RAG with the second shard to obtain second probabilities associated with second tokens used to determine the next token in the generative text;
determine combined probabilities based in part on at least one of the first probabilities and second probabilities obtained from the LLM for tokens included in the first tokens and the second tokens;
select the next token for the generative text from the tokens based at least in part on the combined probabilities;
and
generate, in response to the request, the generative text that includes a word associated with the next token.

9 more elements

A system, comprising:

one or more processors;
and
memory storing program instructions that, when executed by the one or more processors, cause the one or more processors to at least:
determine a data source that includes data for use by one or more large language models (LLMs) implemented with retrieval-augmented generation (RAG);
shard the data source into at least a first shard and a second shard;
receive a request to be fulfilled at least in part by the one or more LLMs implemented with the RAG;
send a first query to the one or more LLMs implemented with the RAG with the first shard to determine a first probability associated with a token used to determine a response;
send a second query to at least one of the one or more LLMs implemented with the RAG with the second shard to determine a second probability associated with the token;
determine a combined probability associated with the token based at least in part on the first probability and the second probability and less than the greater of the first probability and the second probability;
and
select the token based on the combined probability.

8 more elements

Dependencies are inferred from the claim text.