Papers by Jaewon Cheon

1 papers
COUNTDOWN: Contextually Sparse Activation Filtering Out Unnecessary Weights in Down Projection (2025.emnlp-main)

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Challenge: Large language models have created significant computational inefficiencies due to their size and complexity.
Approach: They propose to use a linear combination to deactivate non-essential parameters during inference to reduce computational costs.
Outcome: The proposed methods can omit 90% of computations with performance loss as low as 5.5% ideally, while M-COUNTDOWN provides a predictor-free solution with up to 29.4% better performance preservation compared to existing methods.

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