Assumptions Scalability and Generalization Questions

Ability to identify and critique assumptions in methods, and to reason about how approaches scale and generalize. Topics include what assumptions are required for correctness, how methods behave under dataset growth or distribution shift, computational scaling laws, sample complexity considerations, and strategies to improve generalization or transfer across domains. Candidates should propose concrete experiments or modifications to test robustness and scaling.