Language representations serve as the asymptotic attractor for convergence in independently trained multimodal neural networks due to feature density asymmetry.
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2 Pith papers cite this work. Polarity classification is still indexing.
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PairCoder is a two-agent pair-programming method that leverages toolchain verification oracles to improve LLM generation of verifiable structured artifacts on 17 benchmarks across seven models.
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The Wittgensteinian Representation Hypothesis: Is Language the Attractor of Multimodal Convergence?
Language representations serve as the asymptotic attractor for convergence in independently trained multimodal neural networks due to feature density asymmetry.
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PairCoder++: Pair Programming as a Universal Paradigm for Verified Code-Driven Multimodal and Structured-Artifact Generation
PairCoder is a two-agent pair-programming method that leverages toolchain verification oracles to improve LLM generation of verifiable structured artifacts on 17 benchmarks across seven models.