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Pretrained transformers use little of their depth to follow references in context. Thirteen base models reliably follow only 1.4-3.6 lines, and extra pretrained loops add little. A task-trained rank-8 LoRA at one early layer extends this computation with all model weights frozen. Qwen3-8B improves from 15.5% to 99% exa...
This work forms attack and defense as partially observed state control in SEAD, deriving their design requirements from this shared execution process and constructs an environment-verifiable dataset integrating controlled initial states, replayable tool environments, and task-specific executable checks.
AcFlow is introduced, an inference-time controller that transports intermediate layer image-token activations through a learned concept-conditioned velocity field while keeping the base DiT frozen, and supports the learned velocity field as an adaptive control mechanism.
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