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lost-in-the-middle

topic1 events
papersTODAY 04:00 UTC

Paper Tackles Lost-in-the-Middle Problem in Long-Text Generation

A new arXiv paper addresses how large language models tend to ignore information placed in the middle of long contexts, a problem studied mostly for retrieval tasks rather than long-input-to-long-output generation. The authors introduce a synthetic dataset and evaluation framework for this setting and propose a mitigation approach. The work is a revised cross-listing (v2) on arXiv cs.AI.

long-context/llm/evaluation/dataset