manual-sync 2026-07-02T20:50:21Z local-atlas-guided-flow docs

workspace/docs/cil_format.md

@@ -86,6 +86,10 @@ Learned generator targets:
   and heldout groups report PTR proxy, negative-near rate, and whether the
   nearest proposal is closer to a hidden positive than to hidden negatives. It
   should be reported as support evidence, not as the final learned generator.
+- `scripts/eval_positive_tangent_local_atlas.py` evaluates local chart-neighborhood
+  reuse: for each heldout chart it retrieves train-only positive tangents from
+  nearby observation-language-task charts. This is not the final generator, but
+  it tests whether positive support is locally organized in the atlas.
 - `scripts/train_positive_tangent_cvae.py` trains a first raw-action CVAE over
   train-only positive tangents. The companion
   `scripts/summarize_positive_tangent_cvae_sweep.py` ranks temperature/beta
@@ -99,6 +103,11 @@ Learned generator targets:
   matching in the same keyframe tangent space. Current results should be read
   as a falsification of unguided density flow: useful as a stepping stone, but
   not the final utility-guided atlas generator.
+- `scripts/train_positive_tangent_guided_spline_flow.py` adds the missing
+  contrastive part: a train-only positive-vs-negative utility head guides the
+  same spline flow during sampling. This tests whether the atlas should be a
+  learned local causal utility field over tangent geometry, not just a density
+  model over positive examples.
 
 JSONL shards should preserve complete groups. A group may exceed the target shard size, but it
 should never be split across shards unless an explicit future streaming mode opts into that tradeoff.