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    It is not the case that Systems that succeed on stereotyped narratives systematically fail on syntactically marked constructions like center-embedded clauses, revealing an undischarged dependency on syntax.

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    Reasons For

    1 perspective
    Reason for
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    • 1.Large language models show surprising competence on center-embedded clauses despite training primarily on surface-level narratives, suggesting hidden syntactic capacity.
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    • 2.Poor performance on specific constructions may reflect evaluation methodology rather than fundamental architectural dependency—different metrics yield different conclusions.
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    • 3.Many systems exhibit syntax-like behavior without explicit training on syntax, implying competence emerges from scale rather than requiring undischarged dependencies.
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    Reasons Against

    1 perspective
    Reason against
    ?
    • 1.Language models trained primarily on high-frequency narrative patterns learn statistical associations rather than compositional rules governing recursion.
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    • 2.Center-embedded clauses require maintaining multiple open dependencies simultaneously—a capability distinct from pattern matching in stereotyped text.
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    • 3.Performance gaps between narrative tasks and syntactically complex constructions correlate with training data skew toward naturally-occurring (non-embedded) utterances.
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