UQLM: Uncertainty Quantification for Language Models, is a Python package for UQ-based LLM hallucination detection

[NeurIPS 2025] SECA: Semantically Equivalent and Coherent Attacks for Eliciting LLM Hallucinations

RAG Hallucination Detecting By LRP.

CRoPS (TMLR)

Novel Hallucination detection method

Semi-supervised pipeline to detect LLM hallucinations. Uses Mistral-7B for zero-shot pseudo-labeling and DeBERTa for efficient classification.

Build your own open-source REST API endpoint to detect hallucination in LLM generated responses.

Source code for the paper: Mitigating Hallucination in Security Policy Generation in Large Language Models: A Prompt Ensembling Approach

UQLM: Uncertainty Quantification for Language Models, is a Python package for UQ-based LLM hallucination detection

This repository contains the codebase for the PoC of LLM package hallucination and associated vulnerabilties.