Papers with Information Bottleneck perspective

1 papers
Learning to Maximize Mutual Information for Chain-of-Thought Distillation (2024.findings-acl)

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Challenge: Knowledge distillation is a technique of transferring knowledge from large, complex models to smaller ones.
Approach: They propose a method utilizing chain-of-thought distillation to transfer knowledge from large, complex models to smaller ones by maximizing mutual information of the representation features of the two tasks.
Outcome: The proposed method outperforms the state-of-the-art knowledge distillation method on four datasets.

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