When Calibration Goes Awry: Hallucination in Language Models

When Calibration Goes Awry: Hallucination in Language Models

Explore the phenomenon of hallucinations in language models through this insightful lecture by Adam Kalai from OpenAI. Delve into how calibration, a process naturally encouraged during pre-training, can lead to unexpected hallucinations. Examine the relationship between hallucination rates and domains using the Good-Turing estimator, with a particular focus on notorious sources like paper titles. Gain valuable insights into potential methods for mitigating hallucinations in AI language models. This hour-long talk, part of the Emerging Generalization Settings series at the Simons Institute, presents joint research with Santosh Vempala conducted while Kalai was at Microsoft Research New England.