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title: G0 Hallucination Detector
emoji: 🔍
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 4.44.0
app_file: app.py
pinned: false
license: mit
short_description: Detect when LLMs hallucinate using 3-criterion grounding
---
# G0 Hallucination Detector
Detect when LLMs make things up using a 3-criterion grounding metric.
## How It Works
**G0 = (Tracking × Intervention × Counterfactual)^(1/3)**
- **Tracking:** Does the claim semantically follow from the sources?
- **Intervention:** Would changing the sources change the claim?
- **Counterfactual:** Is the claim uniquely dependent on these sources?
## Scores
- **0.7-1.0:** Grounded - claim is well-supported
- **0.4-0.7:** Partial - some support, may contain unsupported elements
- **0.0-0.4:** Hallucination - claim not supported by sources
## Use Cases
- Verify LLM outputs before production
- Audit RAG pipeline responses
- Research on hallucination detection
## API
```python
import gradio_client
client = gradio_client.Client("crystalline-labs/g0-detector")
result = client.predict(
claim="The Eiffel Tower was built in 1889",
sources="The Eiffel Tower was constructed from 1887 to 1889.",
api_name="/predict"
)
```
Built by Crystalline Labs
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