Papers with converted encoder models

1 papers
Look Both Ways and No Sink: Converting LLMs into Text Encoders without Training (2025.acl-long)

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Challenge: Existing methods for converting large language models into powerful text encoders require extensive training on large datasets.
Approach: They propose a training-free approach that enables bidirectional attention and suppresses the attention sink phenomenon, resulting in superior performance.
Outcome: The proposed approach enables bidirectional attention and suppresses the attention sink phenomenon, resulting in superior performance.

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