FeaturedRetrieval Augmented Generation
Think building your own Retrieval-Augmented Generation (RAG) system will give you a competitive edge? Think again. Companies are sinking months and hundreds of thousands of dollars into in-house AI projects, only to end up with sluggish, unsecure, and overpriced systems that can't hold a candle to existing solutions.
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Vectara’s Hallucination Evaluation Model surpasses 2 million downloads as the fight against LLM hallucinations continues
The upgraded HHEM-2.1 outperforms both GPT-3.5-Turbo and GPT-4 for hallucination detection and is powering our updated HHEM leaderboard.
GPT4o and Gemini-1.5-Flash are fast and cheap, but hallucinate more
Featuring multilinguality, unlimited context window, and calibration – The Hughes Hallucination Evaluation Model (HHEM) v2 is a major upgrade from v1
Why the size of the model does not necessarily determine its likelihood to hallucinate
A new LLM achieves 0% hallucinations and is set to revolutionize RAG
See how Anthropic’s new Claude 3 LLM hallucinates compared to other foundation models in the Hughes Hallucination Evaluation Model (HHEM)
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