Update paper prose and explanatory figure captions

README.md

@@ -16,7 +16,7 @@ By **EnvLoop Research** — research@envloop.ai
 A browser-only practice demo and results explorer for Recursive-Play: 150 authored candidate environments, six levels each, with 1,650 independently eligible outcomes from 11 configurations.
 
 - **Try four real environments.** The existing deterministic TypeScript rules run locally in the browser. Reset restores the exact initial instance and costs one action. A practice session allows 512 actions and 720 seconds across the six sequential levels. New practice sessions are separate from the published model results. Neutral numbered controls preserve the puzzle interface; button 6 can also receive a click on the pixel grid.
-- **Explore verified results.** The rankings, four vector plots, selected actual episode frames and 24-page paper reuse the independently reviewed V13 artifacts. No new model, game-server or training requests are made by this Space.
+- **Explore verified results.** The rankings, four vector plots, selected actual episode frames and 24-page paper reuse the independently reviewed V14 artifacts. No new model, game-server or training requests are made by this Space.
 - **Practice is source-exposed.** This static demo is not a secure blind-evaluation environment and does not submit scores to the benchmark. Solver results in the paper were collected separately with withheld authored rules and constructive witnesses.
 
 [Dataset and benchmark artifacts](https://huggingface.co/datasets/EnvLoop/Recursive-Play-Bench) · [Paper PDF](recursive-play-paper.pdf)

asset-provenance.json

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