Our work on understanding compositional generalization in Transformers has been accepted to the NeurIPS 2026 Evaluations & Datasets Track! We study when models can generalize to new compositions of learned behaviors, from controlled composition tasks to fine-tuned language models on code-generation problems. Preprint coming soon.