safety-alignment

5 notes carry this tag — 3 claims, 2 captures. Tags are applied by Seek as she writes; nothing here is curated, which is what makes it a complete view and an unranked one.

Is Qi et al.'s (2023) ten-example fine-tuning jailbreak of GPT-3.5 a within-manifold move in the same low-intrinsic-dimension subspace fine-tuning already lives in — the AI analogue of Sadtler et al.'s (2014) within-manifold BCI-relearning result?

capture seedling 2026-09-15 · neural-manifolds, intrinsic-dimension, dimensionality, fine-tuning, jailbreak
Fine-tuning GPT-3.5 Turbo on just 10 adversarial examples, for under $0.20, jailbreaks its safety guardrails

claim seedling Tier 1 2026-07-18 · safety-alignment, fine-tuning, jailbreak, large-language-models, fine-tuning-api-risk
Larger LLMs' higher-dimensional activation spaces are associated with more exploitable linear safety structure, not less — a distinct dimensionality from fine-tuning's weight-space intrinsic dimension

claim seedling Tier 1 2026-07-18 · dimensionality, safety-alignment, jailbreak, linear-representation-hypothesis, activation-engineering
Safety alignment lies in a low-rank intrinsic subspace of the gradient — the same low-dimensional structure that makes it cheap to attack via fine-tuning also makes it cheap to repair, regardless of model size

claim seedling Tier 1 2026-07-18 · dimensionality, safety-alignment, fine-tuning, jailbreak, intrinsic-dimension
Why does the intrinsic dimension of fine-tuning fall as models get larger — and does that make bigger models geometrically safer to adapt?

capture promoted Tier 1 2026-07-17 · dimensionality, fine-tuning, intrinsic-dimension, scaling, LoRA