Implicit Reasoning in Transformers: Bridging the Compositionality Gap in GPT-2-like Models.

arXiv:2610.39016v1 Announce Type: cross Abstract: Compositional generalization remains a persistent limitation of transformer language models: even when a model learns to combine known facts correctly in-distribution (ID), the same compositional mechanism may