Attention Residuals may expose cross-layer information flow directly for interpretability
tokenbender · x · 2026-07-28
The post points out an overlooked use of Attention Residuals (AttnRes) for interpretability work.
Because AttnRes gives each layer a learned pseudo-query and an explicit depth-wise weight matrix over earlier blocks, the model effectively exposes cross-layer information flow instead of forcing researchers to infer it indirectly through activation patching, path attribution, or causal tracing.
The author’s takeaway is that this could make interpretability much easier: instead of reverse-engineering who contributed what to the residual stream, you can inspect the layer-to-layer read distribution directly. They note the idea is still preliminary and may have caveats.
Related event: K3 and Attention Residuals Advance LLM Interpretability(3 posts)→
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