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Notes from the token level
Engineering notes and research on attribution, grounding, and what models actually attend to when they answer.
benchmarksresearchJuly 26, 2026 · 8 min read
Self-attention beats asking a model for citations
One model does both jobs: Qwen3.5-9B writes an answer, then either cites it when asked or has its attention read. Reading attention scores 0.744 against 0.644 F1, and returns in 1.2s instead of 53s.
engineeringresearchJuly 10, 2026 · 9 min read
How TokenPath works
Using the attention activations of an open LLM to construct citations — with a raw-Transformers reproduction you can run yourself.
benchmarksresearchJuly 9, 2026 · 10 min read
One answer, four ways to cite it
We benchmark a prompted frontier LLM, Anthropic's Citations API, embedding retrieval, and TokenPath's post-hoc attention on LongBench-Cite — same answer, same judge. Post-hoc matches generation-time citation quality, ~5–6× faster and ~7× cheaper.