LLMGuard: Guarding Against Unsafe LLM Behavior

arXiv:2403.00826v1 Announce Type: cross
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.

abstract arxiv behavior capabilities challenges concerns cs.cl cs.cr cs.lg enterprise inappropriate language language models large language large language models legal llm llms monitors opportunities regulations risk tool type