Papers with off-the-

1 papers
Parallel Context Windows for Large Language Models (2023.acl-long)

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Challenge: Existing efforts to address context window limitation for off-the-shelf LLMs involve training specialized architectures.
Approach: They propose a method that carves a long context into chunks and restricts attention to apply only within each window.
Outcome: The proposed method shows significant improvements on in-context learning tasks with diverse input and output spaces.

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