Question

[keshav12280-blip]

Collective inference quality seems particularly vulnerable when graph neighborhood structure becomes highly asymmetric across subsets of nodes. In those situations, uncertainty propagation can remain statistically stable globally while still producing locally amplified instability for sparse neighborhoods.

This raises an interesting possibility for post-inference calibration strategies conditioned on neighborhood entropy rather than relying exclusively on representation-level regularization.