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Paper: Neural Networks Fail Fodor & Pylyshyn's Systematicity Challenge

By PulseAugur Editorial · [2 sources] ·

A new paper argues that neural networks have not yet met Fodor and Pylyshyn's systematicity challenge, a key puzzle in cognitive science. The authors contend that recent claims suggesting neural networks can explain human systematicity, such as those by Brenden Lake and Marco Baroni, are premature. Their analysis indicates that the proposed meta-learning protocol struggles with out-of-distribution rules and even exhibits unsystematic behavior on some within-distribution problems, leaving the original challenge unmet. AI

IMPACT Challenges the notion that current neural networks can fully replicate human cognitive systematicity, suggesting further research is needed.

RANK_REASON The cluster contains a research paper published on arXiv that analyzes and critiques existing research in AI and cognitive science.

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Paper: Neural Networks Fail Fodor & Pylyshyn's Systematicity Challenge

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The cluster contains a research paper published on arXiv that analyzes and critiques existing research in AI and cognitive science.
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COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Michael Goodale, Salvador Mascarenhas ·

    Fodor and Pylyshyn's Systematicity Challenge Still Stands

    arXiv:2606.14512v1 Announce Type: cross Abstract: The recent successes of neural networks producing human-like language have caused significant stir in cognitive science, with many researchers arguing that classical puzzles about human cognition and challenges to artificial intel…

  2. arXiv cs.AI TIER_1 English(EN) · Salvador Mascarenhas ·

    Fodor and Pylyshyn's Systematicity Challenge Still Stands

    The recent successes of neural networks producing human-like language have caused significant stir in cognitive science, with many researchers arguing that classical puzzles about human cognition and challenges to artificial intelligence are being solved by neural networks. A not…

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