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docs: honest prior-art positioning in README - #24

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docs/anf-honest-positioning
Jul 16, 2026
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docs: honest prior-art positioning in README#24
shreyanshjain7174 merged 1 commit into
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docs/anf-honest-positioning

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Adds a short 'Prior art and honest positioning' section. States plainly that ANF is a supporting internal tool, not a novel format or published research, cites TOON/TRON/TSLN and the independent benchmarks (arXiv 2605.29676, 2606.01326), and clarifies that the token savings come from view extraction, not notation. docs check passes.

ANF is a supporting internal tool, not a novel format or published research.
Acknowledge prior art (TOON/TRON/TSLN) and the independent agentic benchmarks
(arXiv 2605.29676, 2606.01326) showing compact notations give modest,
accuracy-costly gains. State plainly that ANF's savings come from view
extraction, not notation.

Signed-off-by: Shreyansh Sancheti <43677304+shreyanshjain7174@users.noreply.github.com>

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Pull request overview

Adds an explicit “Prior art and honest positioning” section to the README to clarify that ANF is an internal, supporting tool focused on view extraction rather than a novel serialization format, and to reference related prior work and benchmarks.

Changes:

  • Introduces a new README section describing prior art and positioning.
  • Adds benchmark citations and clarifies where token savings come from (view extraction vs. notation).

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Comment thread README.md
## Prior art and honest positioning

ANF is not a novel serialization format, and this is not published research. The
token-efficient-format space is already crowded: TOON, TRON, and TSLN cover
Comment thread README.md
Comment on lines +77 to +80
approach. The "Notation Matters" agentic benchmark (arXiv 2605.29676) finds
compact notations save roughly 18-27% inside real agent loops and cost accuracy.
State-in-context minification (arXiv 2606.01326) reports about 42% with a 12pp
accuracy drop.
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shreyanshjain7174 merged commit 7807d03 into main Jul 16, 2026
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shreyanshjain7174 deleted the docs/anf-honest-positioning branch July 16, 2026 09:11
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2 participants