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Fodor and Pylyshyn's Systematicity Challenge Still Stands

paperactivefodor-and-pylyshyn-s-systematicity-challenge-still-stands-32e37750·1 events·first seen Jun 15, 2026

Aliases: Fodor and Pylyshyn's Systematicity Challenge Still Stands

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Brenden Lake Zenon Pylyshyn Marco Baroni Jerry Fodor Meta-Learning for Compositionality

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5arXiv · cs.CL·Jun 15, 2026·source ↗

Fodor and Pylyshyn's systematicity challenge to neural networks remains unmet, paper argues

A new arXiv preprint argues that recent claims that neural networks have met Fodor and Pylyshyn's systematicity challenge are premature. The authors specifically target Lake and Baroni's meta-learning for compositionality (MLC) protocol, showing it struggles with out-of-distribution rules and behaves unsystematically on many within-distribution problems. The paper concludes that the classical cognitive science challenge — that neural networks cannot explain systematic biconditional dependencies in language and thought — remains unresolved.

Evaluation and Benchmarking AI Safety Research Fodor and Pylyshyn's Systematicity Challenge Still Stands Brenden Lake Zenon Pylyshyn +3 more