From 0d167497b75031fae67b71fa1e7ab12e57c761bb Mon Sep 17 00:00:00 2001 From: YurenHao0426 Date: Mon, 10 Aug 2026 10:50:16 -0500 Subject: results: close BabyAI population predictor rescue --- BABYAI_SHARED_FEEDBACK.md | 19 +++++++++++++++++++ 1 file changed, 19 insertions(+) (limited to 'BABYAI_SHARED_FEEDBACK.md') diff --git a/BABYAI_SHARED_FEEDBACK.md b/BABYAI_SHARED_FEEDBACK.md index 5749949..ea3bd99 100644 --- a/BABYAI_SHARED_FEEDBACK.md +++ b/BABYAI_SHARED_FEEDBACK.md @@ -236,3 +236,22 @@ held-out mean per-cell `R^2 >= 0.8` and residual context RMS at most `0.25` of the original. This ridge fit is an expressivity upper bound, not the proposed hardware learning rule. Passing opens a separate local-delta predictor check; failure closes the population-predictor rescue. + +## P3 outcome: population-linear capacity is insufficient + +All three seeds fail the frozen capacity gate. At initialization, the four +layers have held-out `R^2` between roughly `0.972` and `0.998`, with residual +context RMS ratios between `0.031` and `0.107`. During clean task learning, +the first layer loses identifiability. At epoch 40 its held-out `R^2` is +`0.765`, `0.774`, and `0.752` across seeds, while its residual ratios are +`0.310`, `0.306`, and `0.327`. The worst observed values are `R^2 = 0.7517` +and residual ratio `0.3266`, outside both frozen limits. Later layers remain +more predictable, so the failure is localized but still violates the +every-layer requirement. + +The population map is much stronger than the diagonal predictor, but is not a +stable solution throughout learning. P3 therefore closes the present BabyAI +rescue without a local-delta implementation or another downstream endpoint. +Any future attempt must change what the predictor observes or how early-layer +state is represented; increasing neutral samples, changing ridge strength, or +using task accuracy to select a predictor is outside this protocol. -- cgit v1.2.3