title: Granite Guardian
summary: We introduce the Granite Guardian models, a suite of safeguards designed to
  provide risk detection for prompts and responses, enabling safe and responsible
  use in combination with any large language model (LLM). These models offer
  comprehensive coverage across multiple risk dimensions, including social bias,
  profanity, violence, sexual content, unethical behavior, jailbreaking, and
  hallucination-related risks such as context relevance, groundedness, and answer
  relevance for retrieval-augmented generation (RAG). Trained on a unique dataset
  combining human annotations from diverse sources and synthetic data, Granite
  Guardian models address risks typically overlooked by traditional risk
  detection models, such as jailbreaks and RAG-specific issues. With AUC scores
  of 0.871 and 0.854 on harmful content and RAG-hallucination-related benchmarks
  respectively, Granite Guardian is the most generalizable and competitive model
  available in the space. Released as open-source, Granite Guardian aims to
  promote responsible AI development across the community.
    https://github.com/ibm-granite/granite-guardian
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paper_title: Granite Guardian
paper_summary: We introduce the Granite Guardian models, a suite of safeguards designed to
  provide risk detection for prompts and responses, enabling safe and responsible
  use in combination with any large language model (LLM). These models offer
  comprehensive coverage across multiple risk dimensions, including social bias,
  profanity, violence, sexual content, unethical behavior, jailbreaking, and
  hallucination-related risks such as context relevance, groundedness, and answer
  relevance for retrieval-augmented generation (RAG). Trained on a unique dataset
  combining human annotations from diverse sources and synthetic data, Granite
  Guardian models address risks typically overlooked by traditional risk
  detection models, such as jailbreaks and RAG-specific issues. With AUC scores
  of 0.871 and 0.854 on harmful content and RAG-hallucination-related benchmarks
  respectively, Granite Guardian is the most generalizable and competitive model
  available in the space. Released as open-source, Granite Guardian aims to
  promote responsible AI development across the community.
    https://github.com/ibm-granite/granite-guardian
paper_ai_summary: Granite Guardian models provide comprehensive risk detection for prompts and responses in large language models (LLM), addressing social bias, profanity, violence, sexual content, unethical behavior, jailbreaking, and retrieval-augmented generation (RAG) hallucination risks.
paper_ai_keywords: Granite Guardian models large language model (LLM) risk detection social bias profanity violence sexual content unethical behavior jailbreaking retrieval-augmented generation (RAG) hallucination risks context relevance groundedness answer relevance AUC scores