In their article, Jim Waldo and Soline Boussard delve into the phenomenon of large language models (LLMs) hallucinating responses in their text generation. Despite GPTs’ impressive capabilities in answering questions and engaging in conversations, they tend to produce nonfactual or nonsensical responses that can disseminate false information. The authors highlight a case where a lawyer unknowingly used a ChatGPT to generate fictional case citations, emphasizing the risks of misleading outcomes. The article also explores how GPTs’ training on massive amounts of language data affects the accuracy of their responses, shedding light on the importance of understanding the underlying mechanisms behind LLMs’ functioning.
https://queue.acm.org/detail.cfm?id=3688007