Papers by Zujing Liu

1 papers
Bypass Back-propagation: Optimization-based Structural Pruning for Large Language Models via Policy Gradient (2025.acl-long)

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Challenge: Recent pruning methods rely on heuristically hand-crafted metrics, leading to suboptimal performance.
Approach: They propose a method that optimizes pruning masks by minimizing back-propagation . they learn an underlying Bernoulli distribution to sample binary pruning mask samples .
Outcome: The proposed method is able to support global and heterogeneous pruning without back-propagation.

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