Unverified50% confidenceFactExact time
The paper "Found in the Middle" (Hsieh et al., ACL Findings 2024) attributes the lost-in-the-middle effect to the attention mechanism: tokens at the beginning and end of the input receive more attention regardless of their actual relevance.
1
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50%
Confidence
Long-term
Relevance
10/12/2026
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Related Claims
UnverifiedA 2023 Stanford University paper titled 'Lost in the Middle' found that models pay significantly less attention to information in the middle of the context window than at the beginning and end, exhibiting a U-shaped attention distribution.77% similarVerified研究表明当上下文过长时，模型对中间部分信息的注意力会显著下降，即"Lost in the Middle"现象74% similarUnverifiedCurrent frontier models face attention decay when handling long-range dependencies, with the ability to maintain consistency of early-established settings declining significantly as context length increases.74% similarUnverifiedCurrent large models do not have a true persistent memory mechanism, and as the number of conversation turns increases, the weight of early requirement descriptions in the attention mechanism gradually decays.72% similar
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