# How to measure hallucination [INSIDE: LLMS’ INTERNAL STATES RETAIN THE POWER OF HALLUCINATION DETECTION](https://openreview.net/pdf?id=Zj12nzlQbz) - ICLR2024 ![image](https://hackmd.io/_uploads/B1cF8MOyR.png) ![image](https://hackmd.io/_uploads/HJ0-vM_1R.png) [A Mathematical Investigation of Hallucination and Creativity in GPT Models](https://www.mdpi.com/2227-7390/11/10/2320) ![image](https://hackmd.io/_uploads/S1RPbrOk0.png) [Measuring and Reducing LLM Hallucination without Gold-Standard Answers via Expertise-Weighting](https://arxiv.org/pdf/2402.10412.pdf) ![image](https://hackmd.io/_uploads/ryEoGrO1A.png) ![image](https://hackmd.io/_uploads/SkU5zr_JA.png) [KCTS: Knowledge-Constrained Tree Search Decoding with Token-Level Hallucination Detection](https://aclanthology.org/2023.emnlp-main.867.pdf) - EMNLP2023 ![image](https://hackmd.io/_uploads/r13VQBuk0.png =80%x) [AutoHall: Automated Hallucination Dataset Generation for Large Language Models](https://arxiv.org/pdf/2310.00259.pdf) ![image](https://hackmd.io/_uploads/BkryuBuyC.png) [HaluEval: A Large-Scale Hallucination Evaluation Benchmar for Large Language Models](https://arxiv.org/pdf/2305.11747.pdf) [Semantic Consistency for Assuring Reliability of Large Language Models](https://arxiv.org/pdf/2308.09138.pdf)