Autoregressive large language models routinely generate factually incorrect outputs with high decoding confidence, limiting their deployment in high-stakes workflows

Autoregressive large language models (LLMs) routinely generate factually incorrect outputs with high decoding confidence, limiting their deployment in high-stakes workflows.

http://arxiv.org/abs/2608.27165v1