RAGE Against the Machine: Retrieval-Augmented LLM Explanations

Autor:	Rorseth, Joel, Godfrey, Parke, Golab, Lukasz, Srivastava, Divesh, Szlichta, Jaroslaw
Rok vydání:	2024
Předmět:	Computer Science - Computation and Language Computer Science - Artificial Intelligence Computer Science - Information Retrieval
Druh dokumentu:	Working Paper
Popis:	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. Comment: Accepted by ICDE 2024 (Demonstration Track)
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2405.13000 Zobrazit plný text záznamu View this record from Arxiv