MUMBAI, India, April 20 -- Intellectual Property India has published a patent application (202514094961 A) filed by Google Llc, Mountain View, U.S.A., on Oct. 3, 2025, for 'fine-tuning a target generative neural network using an improvement generative neural network.'
Inventor(s) include Wang, Qifei; Fan, Ying; Zhao, Yang; Ramachandran, Deepak; Yang, Feng; and Jain, Rahul Anant.
The application for the patent was published on April 17, under issue no. 16/2026.
According to the abstract released by the Intellectual Property India: "Methods, systems, and apparatuses, including computer programs encoded on computer storage media, for training a target generative neural network over a plurality of training iterations. At each iteration, a first data item is generated by processing a conditioning input using the target generative neural network. An improvement generative neural network then processes the first data item and the conditioning input to generate a second, preferred data item. A training example is generated that includes the first and second data items and indicates that the second data item is preferred over the first. The target generative neural network is then trained on this training example. By using this iterative process to dynamically generate preference data, the described techniques improve the performance of the generative neural network beyond the limitations of static, offline datasets without requiring computationally expensive reward models or external human annotation."
Disclaimer: Curated by HT Syndication.
