cvs-health/uqlm
UQLM: Uncertainty Quantification for Language Models, is a Python package for UQ-based LLM hallucination detection
This tool helps people who use large language models (LLMs) to detect when the LLM might be generating incorrect or fabricated information, known as "hallucinations." You provide text prompts to an LLM, and this tool analyzes the responses to give you a confidence score, indicating how likely the answer is to be accurate. This is useful for anyone relying on LLM outputs for critical tasks, such as content creators, researchers, or customer service managers.
1,121 stars. Actively maintained with 33 commits in the last 30 days. Available on PyPI.
Use this if you need to quickly assess the trustworthiness of responses generated by large language models and want to reduce the risk of acting on false information.
Not ideal if you primarily need to improve the underlying accuracy of your LLM rather than just detecting potential errors in its outputs.
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1,121
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116
Language
Python
License
Apache-2.0
Category
Last pushed
Mar 12, 2026
Commits (30d)
33
Dependencies
14
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