In Loving memory of Simon Mark Hughes... Quickstart: try HHEM 2.1 Open Live Demo 👉 Launch Interactive Demo No setup required, runs in your browser 💡 Quick test : Try inputting "The capital of France is Berlin" as premise and "The capital of France is Paris" as hypothesis to see HHEM detect this factual but hallucinated case. HHEM 2.1 Open is the latest open source version of Vectara's HHEM series models for detecting hallucinations in LLMs. These are particularly useful in the context of building retrieval augmented generation (RAG) applications or Agentic workflows, where a set of facts is summarized by an LLM, and HHEM can be used to measure the extent to which this summary is factually consistent with the facts. Hallucination Detection 101 By "hallucinated" or "factually inconsistent", we mean that a text (hypothesis, to be judged) is not supported by another text (evidence/premise, given). You always need two pieces of text to determine whether a text is hallucinated or not. When applied to RAG or AI Agents, the LLM is provided with several pieces of text (often called facts or context) retrieved from some dataset, and a hallucination would indicate that the summary (hypothes…
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