The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models

6 January 2024

Papers citing "The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models"

8 / 8 papers shown

Title
aiXamine: Simplified LLM Safety and Security Fatih Deniz Dorde Popovic Yazan Boshmaf Euisuh Jeong M. Ahmad Sanjay Chawla Issa M. Khalil ELM 72 0 0 21 Apr 2025
OAEI-LLM-T: A TBox Benchmark Dataset for Understanding Large Language Model Hallucinations in Ontology Matching Zhangcheng Qiang Kerry Taylor Weiqing Wang Jing Jiang 52 0 0 25 Mar 2025
FaithEval: Can Your Language Model Stay Faithful to Context, Even If "The Moon is Made of Marshmallows" Yifei Ming Senthil Purushwalkam Shrey Pandit Zixuan Ke Xuan-Phi Nguyen Caiming Xiong Shafiq R. Joty HILM 110 16 0 30 Sep 2024
How Language Model Hallucinations Can Snowball Muru Zhang Ofir Press William Merrill Alisa Liu Noah A. Smith HILM LRM 78 246 0 22 May 2023
The Intended Uses of Automated Fact-Checking Artefacts: Why, How and Who M. Schlichtkrull N. Ousidhoum Andreas Vlachos 109 17 0 27 Apr 2023
The Internal State of an LLM Knows When It's Lying A. Azaria Tom Michael Mitchell HILM 216 297 0 26 Apr 2023
Generate rather than Retrieve: Large Language Models are Strong Context Generators W. Yu Dan Iter Shuohang Wang Yichong Xu Mingxuan Ju Soumya Sanyal Chenguang Zhu Michael Zeng Meng-Long Jiang RALM AIMat 215 318 0 21 Sep 2022
Training language models to follow instructions with human feedback Long Ouyang Jeff Wu Xu Jiang Diogo Almeida Carroll L. Wainwright ... Amanda Askell Peter Welinder Paul Christiano Jan Leike Ryan J. Lowe OSLM ALM 301 11,730 0 04 Mar 2022