The use of web-scale and unfiltered pretraining data containing inconsistencies, biases, and outdated or false information can negatively affect large language models during training, as noted by Shuster et al. (2022), Chen et al. (2023), and Weidinger et al. (2022).

Authors

• Person: Not available Organization: Frontiers
  Survey and analysis of hallucinations in large language models

Sources

• Survey and analysis of hallucinations in large language models www.frontiersin.org Frontiers via serper

Referenced by nodes (1)

• Large Language Models concept