How do language models balance pre-existing knowledge with new information during in-context learning? In this keynote session, Jerry will reveal how larger models can override semantic priors, adapt to arbitrary input-label mappings, and even perform linear classification in challenging settings. We'll also discuss the impact of instruction tuning on these abilities.