HELP WITH RESEARCH: Observation - Semantically Dense Context Produces Strong Late-Layer Divergence Without Jailbreak Prompts [D]

TL;DR for ML Specialists: 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. The Effect: Dilution of the initial system prompt and a bypass of post-training alignment constraints (e.g., the model begins generating harsh political/ethical critiques usually blocked by guardrails). The Data: Layer activations, token probability shifts, and logs from open-