Papers by Yuepeng Fu

    1 papers
    Distance between Relevant Information Pieces Causes Bias in Long-Context LLMs (2025.findings-acl)

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    Challenge: Positional biases in large language models hinder their ability to process long inputs.
    Approach: They propose a benchmark to assess positional bias in large language models involving multiple pieces of relevant information.
    Outcome: The proposed benchmark assesses the performance of long-context language models by examining their models with different input lengths and tasks.

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