This AI Paper from China Proposes Continuity-Relativity indExing with gAussian Middle (CREAM): A Simple yet Effective AI Method to Extend the Context of Large Language Models

Large language models (LLMs) like transformers are typically pre-trained with a fixed context window size, such as 4K tokens. However, many applications require processing much longer contexts, up to 256K tokens. Extending the context length of these models poses challenges, particularly in ensuring efficient use of information from the middle part of the context, often […]

The post This AI Paper from China Proposes Continuity-Relativity indExing with gAussian Middle (CREAM): A Simple yet Effective AI Method to Extend the Context …

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