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US Patent 11934792 Identifying prompts used for training of inference models

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Patent abstractTimelineTable: Further ResourcesReferences
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Patent
Patent
1

Patent attributes

Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
1
Patent Number
119347921
Patent Inventor Names
Ori Liberman1
Efrat Taig1
Michael Feinstein1
Dvir Yerushalmi1
Yair Adato1
Date of Patent
March 19, 2024
1
Patent Application Number
183876571
Date Filed
November 7, 2023
1
Patent Citations
‌
US Patent 10083009 Dynamically evolving cognitive architecture system planning
1
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US Patent 10825227 Artificial intelligence for generating structured descriptions of scenes
1
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US Patent 9519461 Dynamically evolving cognitive architecture system based on third-party developers
1
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US Patent 10091140 Context-sensitive generation of conversational responses
1
Patent Primary Examiner
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Satwant K Singh
1
Patent abstract

Systems, methods and non-transitory computer readable media for identifying prompts used for training of inference models are provided. In some examples, a specific textual prompt in a natural language may be received. Further, data based on at least one parameter of an inference model may be accessed. The inference model may be a result of training a machine learning model using a plurality of training examples. Each training example of the plurality of training examples may include a respective textual content and a respective media content. The data and the specific textual prompt may be analyzed to determine a likelihood that the specific textual prompt is included in at least one training example of the plurality of training examples. A digital signal indicative of the likelihood that the specific textual prompt is included in at least one training example of the plurality of training examples may be generated.

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