首页|Patent Application Titled 'Dialog Management For Large Language Model-Based (Llm -Based) Dialogs' Published Online (USPTO 20240311575)
Patent Application Titled 'Dialog Management For Large Language Model-Based (Llm -Based) Dialogs' Published Online (USPTO 20240311575)
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According to news reporting originatin g from Washington, D.C., by NewsRx journalists, a patent application by the inve ntors Baeuml, Martin (Wollerau, CH); Bailey, Alexander (Wollerau, CH); Bragagnol o, Jonas (Affoltern am Albis, CH); D'Halluin, Florent (Zurich, CH); Strohman, Tr evor (Sunnyvale, CA, US), filed on March 17, 2023, was made available online on September 19, 2024. No assignee for this patent application has been made. Reporters obtained the following quote from the background information supplied by the inventors: "Large language models (LLMs) are particular types of machine learning models that can perform various natural language processing (NLP) tasks , such as language generation, machine translation, and questionanswering. Thes e LLMs are typically trained on enormous amounts of diverse data including data from, but not limited to, webpages, electronic books, software code, electronic news articles, and machine translation data. Accordingly, these LLMs leverage th e underlying data on which they were trained in performing these various NLP tas ks. For instance, in performing a language generation task, these LLMs can proce ss a natural language (NL) based input that is received from a client device, an d generate a NL based output that is responsive to the NL based input and that i s to be rendered at the client device. In many instances, and in generating the NL based output that is responsive to the NL based input, these LLMs can also pr ocess a corresponding dialog context for respective dialogs with respective user s that is built throughout the respective dialogs. However, in generating the NL based output utilizing these LLMs and by processing the corresponding dialog co ntexts, the respective users can provide NL based inputs that build correspondin g dialog contexts that can result in undesirable NL based outputs being generate and rendered. Accordingly, there is a need in the art for managing these corres ponding dialog contexts and/or NL based outputs generated based at least in part on processing these corresponding dialog contexts."
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