RFE‑Core2 — Current Understanding (June 9th 2026) [R]

Reddit r/MachineLearning / 6/10/2026

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Key Points

The update concludes that the generator is the primary bottleneck because it concentrates most energy into a dominant shared (common-mode) direction, keeping regime means highly collinear across dimensions.
The reflective loop acts as a rank-independent moat that reconstitutes representations back toward an established anchor, yielding near-zero migration even when orthogonal deterministic pairs are tested.
Fix 2, described as a loop-loosening mechanism, is largely dormant on real token regimes; its reported gains were likely overstated by mock settings, since real-token triggering only produces limited migration (+0.024) with 0% manipulation at gain 0.6.
Dimensionality is not the main lever; instead, the report argues that training should shift regime differences into high-energy, separable directions so downstream tools can meaningfully act on them.
The report aggregates results from a full probe arc through June 9, including ablations, diversity audits, live-generator Fix 2 evaluation, and dimensionality sweeps, sharpening the overall causal picture.

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