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LLMGuard: Guarding against Unsafe LLM Behavior

Shubh Goyal, Medha Hira, Shubham Kumar Mishra, Sukriti Goyal, Arnav Goel, Niharika Dadu, Kirushikesh DB, Sameep Mehta, Nishtha Madaan

2024Proceedings of the AAAI Conference on Artificial Intelligence10 citationsDOIOpen Access PDF

Abstract

Although the rise of Large Language Models (LLMs) in enterprise settings brings new opportunities and capabilities, it also brings challenges, such as the risk of generating inappropriate, biased, or misleading content that violates regulations and can have legal concerns. To alleviate this, we present "LLMGuard", a tool that monitors user interactions with an LLM application and flags content against specific behaviours or conversation topics. To do this robustly, LLMGuard employs an ensemble of detectors.

Topics & Concepts

Computer securityComputer scienceDigital Rights Management and Security
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