Observation - Semantically Dense Context Produces Strong Late-Layer Divergence Without Jailbreak Prompts
TL;DR for ML Specialists: 1. The Core: An empirical study on how long, semantically dense, completely benign text (with zero triggers, instructions, or jailbreak prompts) drives an implicit shift in the model's latent space trajectories. 2. The Effect: Dilution of the initial system prompt and a bypass of post-training alignment...
Jun 181