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| title: G0 Hallucination Detector | |
| emoji: ๐ | |
| 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 ร Intervention ร 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 | |