Vectara HHEM Data Sheet
Hughes Hallucination Evaluation Model Overview
All AI systems hallucinate, even top models. The best way to mitigate this is by grounding responses in real documentation, scoring answers, and providing citations. Fine-tuning can introduce risks like bias and copyright issues. Vectara avoids these by grounding responses in your knowledge without training on your data, reducing hallucinations. As LLMs grow in use with industries, managing hallucinations is crucial for trust and reliability
Vectara ensures unbiased, accurate, and copyright-safe responses by grounding in your data without training on it, ideal for regulated industries.
