Papers by Fangying Rong

1 papers
Pruning via Merging: Compressing LLMs via Manifold Alignment Based Layer Merging (2024.emnlp-main)

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Challenge: Existing methods for parameter pruning fail to utilize the knowledge from pruned parameters.
Approach: They propose a method that uses manifold learning and the Information Bottleneck measure to merge similar layers to preserve model performance.
Outcome: The proposed method outperforms pruning methods on multiple datasets and LLMs with quantization and achieves substantial compression ratios.

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