Papers with SKR

2 papers
Supportiveness-based Knowledge Rewriting for Retrieval-augmented Language Modeling (2025.findings-naacl)

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Challenge: Recent advances in large language models (LLMs) have significantly enhanced their performance in various natural language processing tasks.
Approach: They propose a robust and pluggable knowledge rewriter that is optimized for LLM generation by supporting the model's supportiveness.
Outcome: The proposed model can be used to rewrite knowledge in a supervised manner.
Self-Knowledge Guided Retrieval Augmentation for Large Language Models (2023.findings-emnlp)

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Challenge: Large language models (LLMs) have shown superior performance without task-specific fine-tuning due to the computational costs.
Approach: They propose a method which lets LLMs refer to the questions they have previously encountered and adaptively call for external resources when dealing with new questions.
Outcome: The proposed method outperforms chain-of-thought based and fully retrieval-based methods on multiple datasets and outperformed chain- of-though, chatGPT and InstructGPT.

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