Hallucination Detector

What it does

Hallucination Detector is a system that goes beyond basic fact-checking, using statistical analysis and weighted scoring to identify false or unsupported outputs from LLMs. It provides real-time detection, confidence scoring, coverage across 50+ domains, and model performance tracking. Errors are classified by severity, and accuracy improves through statistical accumulation. With dual-axis scoring, precise risk weights, and trust dampening, it delivers higher reliability and AI transparency.

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  Bullshit Detector2023 · ▲75

  Detects hallucinations (false info) in AI-generated content

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  Open-source model and scorecard for measuring hallucinations in LLMs2023 · vectara.com · ▲65

  Hi all! This morning, we released a new Apache 2.0 licensed model on HuggingFace for detecting hallucinations in retrieval augmented generation (RAG) systems. What we've found is that even when given a "simple" instruction like "summarize the following news article," every LLM that's available hallucinates to some extent, making up details that never existed in the source article -- and some of them quite a bit. As a RAG provider and proponents of ethical AI, we want to see LLMs get better at this. We've published an open source model, a blog more thoroughly describing our methodology (and…

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  Athina AI2024 · athina.ai · ▲509

  Monitor LLMs and automatically detect hallucinations in prod

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  Truth MirrorJun 2026 · wuyijia.gumroad.com · ▲2

  Real-time AI hallucination detection. Don't trust, verify.

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  LLM Sandbox by Dioptra2023 · dioptra.ai · ▲101

  Everything you need to evaluate & improve prompts and LLMs

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  LettuceDetect – Lightweight hallucination detector for RAG pipelines2025 · github.com · ▲10

  Hallucinations are still a major blocker for deploying reliable retrieval-augmented generation (RAG) systems, especially in complex domains like medical or legal. Most existing hallucination detectors rely on full LLM inference (expensive, slow), or struggle with long-context inputs. I built LettuceDetect — an open-source, encoder-only framework that detects hallucinated spans in LLM-generated answers based on the retrieved context. No LLMs needed, and it much more efficiently. Highlights: - Token-level hallucination detection (unsupported spans flagged based on retrieved evidence) - Built…

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  Boing▲782

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