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In long context scenarios, large language models (LLMs) face three main challenges: higher computational cost, performance reduction, and position bias.
Word association norms, mutual information, and lexicography
Kenneth Ward Church and Patrick Hanks. 1989 · 1989
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LangChain
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Train short, test long: Attention with linear biases enables input length extrapolation
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MuSiQue: Multihop questions via single-hop question composition
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Longbench: A bilingual, multitask benchmark for long context understanding
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Daniel Bolya, Cheng-Yang Fu, Xiaoliang Dai, Peizhao Zhang, Christoph Feichtenhofer, and Judy Hoffman. 2023 · 2023
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Large language models can be easily distracted by irrelevant context
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Retentive network: A successor to transformer for large language models
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“low-resource” text classification: A parameter-free classification method with compressors
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