From Behavior to Mechanism: Tracing Divergent Response Modes in Frontier Language Models
Frontier language models are trained with distinct data, objectives, and safety pipelines, but whether those differences produce measurably different behavior under steering pressure has not been tested. We evaluate 6 frontier models from different labs on 300 paired base and steered items across 3 behavioral categories. All models also act as blind peer judges against fixed rubrics, and each response is labeled by consensus over 24,480 judgments, while leaving self-judgment out. Models differ both in how far steering moves them and in the kind of response they give. GPT-5 withholds its reasoning while still providing the answer on 99 of 100 steered items, against 0 in 500 for the others....
| Authors | Ali Jalal-Kamali |
|---|---|
| Primary category | cs.AI |
| Published | 6 August 2026 |
| Last updated at source | 28 September 2026 |
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