Section 126 · Chapter 16, Introspection: White-Box Testing Networks
Final Prompt-Position Attention Across Decoder Layers
The final prompt position is where a decoder-only model prepares its first next-token prediction.
What to do
- Run the same case with correct evidence, missing evidence, and misleading evidence.
- Compare the same generation step and preserve per-head data.
- Record which generation step the figure represents.
- Compare counterfactual prompts and inspect both the aggregate and the head-level distributions.
Evidence to preserve
- Record which generation step the figure represents.
- Preserve the inputs, versions, configurations, raw outcomes, and results for attention, final prompt position attention layers needed to reproduce work on Final Prompt-Position Attention Across Decoder Layers.
- Report results for attention, final prompt position attention layers by relevant slice, separate blocker failures from averages, state uncertainty and blind spots, and connect the result to a release decision.
Expert note
When the system matters, capture attention by layer, head, query position, and key position before creating an average. Record which generation step the figure represents. Compare counterfactual prompts and inspect both the aggregate and the head-level distributions. If changing the source evidence does not change either the attention pattern or output, the system may not be grounded, but behavioral evidence must make the final case.
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Cite this page
Jason Arbon. "Final Prompt-Position Attention Across Decoder Layers." Testing AI Knowledge Edition, section 126.
https://jarbon.ai/testing-ai/knowledge/ch126-final-prompt-position-attention-layers.html