Timeline of large language models

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Year Month and date Event type Details
2023 March 1 Study A paper introduces a method to train language models like ChatGPT to understand concepts precisely using succinct representations based on category theory. The representations provide concept-wise invariance properties and a new learning algorithm that can accurately learn complex concepts or fix misconceptions. The approach also allows for the generation of a hierarchical decomposition of the representations, which can be manually verified by examining each part individually.[1]

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  1. Yuan, Yang (2023). "Succinct Representations for Concepts". doi:10.48550/arXiv.2303.00446.