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LMs as Task-Specific Knowledge Bases: An Interpretability Analysis

A research paper investigating the interpretability and knowledge representation in large language models.

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LMs as Task-Specific Knowledge Bases: An Interpretability Analysis

By Amit Elhelo, Amir Globerson, Mor GevaarXiv
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The authors analyze whether large language models (LMs) can be viewed as task-specific knowledge bases. They find that LMs encode knowledge in a task-specific manner, undermining the 'knowledge base' analogy.

The study also explores the implications for the reliability and controllability of factual knowledge in LMs.

Abstract

The authors analyze whether large language models (LMs) can be viewed as task-specific knowledge bases. They find that LMs encode knowledge in a task-specific manner, undermining the 'knowledge base' analogy. The study also explores the implications for the reliability and controllability of factual knowledge in LMs.

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language modelsknowledge representationinterpretability analysistask-specific knowledge basesfactual knowledgeLarge Language ModelsAI AgentsAgent MemorySemantic Interoperability
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