RAGE Against the Machine: Retrieval-Augmented LLM Explanations

• URL: http://arxiv.org/abs/2405.13000v1
• Date: Sat, 11 May 2024 19:08:38 GMT
• Title: RAGE Against the Machine: Retrieval-Augmented LLM Explanations
• Authors: Joel Rorseth, Parke Godfrey, Lukasz Golab, Divesh Srivastava, Jaroslaw Szlichta,
• Abstract summary: RAGE is an interactive tool for explaining Large Language Models (LLMs) Our explanations are counterfactual in the sense that they identify parts of the input context that, when removed, change the answer to the question posed to the LLM. RAGE includes pruning methods to navigate the vast space of possible explanations, allowing users to view the provenance of the produced answers.
• Score: 17.707251978644486
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This paper demonstrates RAGE, an interactive tool for explaining Large Language Models (LLMs) augmented with retrieval capabilities; i.e., able to query external sources and pull relevant information into their input context. Our explanations are counterfactual in the sense that they identify parts of the input context that, when removed, change the answer to the question posed to the LLM. RAGE includes pruning methods to navigate the vast space of possible explanations, allowing users to view the provenance of the produced answers.

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