Papers by Zhentao Tan

    1 papers
    Llama SLayer 8B: Shallow Layers Hold the Key to Knowledge Injection (2024.findings-emnlp)

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    Challenge: Existing methods to augment pre-trained large language models require extensive computational efforts and massive data volumes, challenging the widespread accessibility of LLM research.
    Approach: They propose a post-pretraining strategy of selectively enhancing shallow layers while pruning less effective deep ones to augment pretrained large language models.
    Outcome: The proposed approach improves performance on the corpus of code & math and a legal corpus and is widely applicable.

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