| CPC G10L 15/183 (2013.01) [G06F 40/279 (2020.01); G06N 3/045 (2023.01); G06N 3/08 (2013.01)] | 20 Claims |

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8. A system for predicting an object of a language based on adapting aspects of a language model, the system comprises:
a processor, and
a memory storing computer-executable instructions that when executed by the processor cause the system to:
receive an input symbol of a plurality of input symbols of the language in series;
receive a set of auxiliary data, wherein the auxiliary data is distinct from the input symbol, and the set of auxiliary data represents a latent topic of the plurality of input symbols of the language according to a bag-of-words model;
generate, based on the received input symbol, an intermediate state symbol using a first neural network;
generate, based on the generated intermediate state symbol and the received set of auxiliary data, an output symbol following the input symbol as a result of predicting the object using a second neural network, thereby adapting the output symbol to the latent topic of the plurality of input symbols of the language according to the bag-of-words model, wherein the second neural network comprises a plurality of hidden layers, and each hidden layer of the plurality of hidden layers receives at least a part of the generated intermediate state symbol and a distinct auxiliary data of the set of auxiliary data as input.
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