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LLMGuard: Guarding Against Unsafe LLM Behavior

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arxiv 2403.00826 v1 pith:AD5L2DET submitted 2024-02-27 cs.CL cs.CRcs.LG

Shubh Goyal , Medha Hira , Shubham Mishra , Sukriti Goyal , Arnav Goel , Niharika Dadu , Kirushikesh DB , Sameep Mehta
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Nishtha Madaan
This is my paper · ORCID
classification cs.CLcs.CRcs.LG
keywords llmguardbringscontentalleviatealthoughapplicationbehaviorbehaviours
verification ladder T0 review T1 audit T2 compute T3 formal
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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.

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