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

CREAM is a practical AI solution that extends the context length of large language models (LLMs), efficiently addressing the "Lost-in-the-Middle" problem. It manipulates position indices and uses truncated Gaussian sampling to focus on the middle part of the context during fine-tuning. This approach allows effective performance on extended contexts up to 256K tokens. By ensuring continuity and relativity in positional encoding, CREAM outperforms existing methods in retrieving information from long contexts and alleviating the "Lost-in-the-Middle" issue. It shows superior performance in long-context understanding tasks, question-answering, and summarization tasks. Overall, CREAM offers a practical solution to the "Lost-in-the-Middle" problem by efficiently extending the context length of LLMs and improving performance in long-context scenarios. For those interested in evolving their company with AI, it's essential to consider practical AI solutions such as CREAM. Key steps include identifying automation opportunities, defining KPIs, selecting the right AI tools, and implementing gradually. For AI KPI management advice and continuous insights into leveraging AI, connect with us at hello@itinai.com and follow our Telegram or Twitter. We also have the AI Sales Bot from itinai.com/aisalesbot, designed to automate customer engagement 24/7 and manage interactions across all customer journey stages. This can redefine your sales processes and customer engagement. You can find us on AI Lab in Telegram @itinai for free consultation and also follow us on Twitter – @itinaicom for more updates.