Papers with small source LM

1 papers
Augmentation-Adapted Retriever Improves Generalization of Language Models as Generic Plug-In (2023.acl-long)

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Challenge: Prior work on retrieval augmentation fine-tuned the retriever and the LM, making them closely coupled.
Approach: They propose a generic retrieval plug-in that can be used to fine-tune retrieval augmentation and a LM to learn a user's preferences.
Outcome: The proposed retriever improves the generalization of large language models on the MMLU and PopQA datasets by learning LM’s preferences from a known source LM .

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