Review for NeurIPS paper: A Benchmark for Systematic Generalization in Grounded Language Understanding

The paper proposes a new benchmark called gSCAN, for learning compositional and grounded natural language understanding. The argument is that to evaluate compositional generalization, situated language understanding (grounding) is necessary. It evaluates eight types of compositional generalization methods with the benchmark. The conclusion is that gSCAN can be used as a useful benchmark. Strength • A new benchmark dataset is created.