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Building Student Module For Large Language Models
  • Tong Guo
Tong Guo

Corresponding Author:[email protected]

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Abstract

The current large language models (LLMs) mainly lacks this capability: autonomous learning capability. Also, we can not prepare all the data/knowledge in the world for LLMs. We propose Learning In Conversation (LIC) to solve the problem to let human teach machine to refresh/expand its data/knowledge automatically by natural language conversation. LIC system is an AI system that contains many deep learning tasks. LIC system provide the natural language interface to let machine to learn new data/knowledge in conversation interacting with human automatically. It is critical, but except for the developers of the AI system, others have no natural language interface to do this education for machine. Based on large language models (LLMs) conversation ability, we train an additional intent recognition model to determine when the AI system need to learn new data/knowledge. We add a module for editing the training dataset of LLMs. We propose the methods to implement our idea and discuss the reasons why we design these methods.