Papers with VRAM consumption

1 papers
PEK: A Parameter-Efficient Framework for Knowledge-Grounded Dialogue Generation (2024.findings-acl)

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Challenge: Pre-trained language models have shown great dialogue generation capability in different scenarios, but the huge VRAM consumption when fine-tuning them is one of their drawbacks.
Approach: They propose a parameter-efficient framework for knowledge-enhanced dialogue generation that leverages external knowledge documents and knowledge graphs to enhance its generation capabilities.
Outcome: The proposed framework outperforms baseline methods on multiple evaluation metrics on Wizard of Wikipedia and CMU_DoG datasets.

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