NLI autonomously discovers a vocabulary of primitive operations and interprets variable-length programs via a neural executor, allowing end-to-end training and gradient-based test-time adaptation that outperforms prior methods on combinatorial generalization tasks.
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4 Pith papers cite this work. Polarity classification is still indexing.
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Creativity is defined as meta-learning where a frozen diffusion creator optimizes candidates for rapid improvement by an adapting appraiser such as an autoencoder or CLIP adapter.
A neurosymbolic model augments Swin Transformers with focal sets and fuzzy logic to produce calibrated hierarchical image classifications that respect logical constraints.
Establishes a uniform Bahadur representation for sieve M-estimators under temporal dependence and constructs valid simultaneous confidence regions using Gaussian approximation and self-convolved bootstrap.
citing papers explorer
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Gradient-Based Program Synthesis with Neurally Interpreted Languages
NLI autonomously discovers a vocabulary of primitive operations and interprets variable-length programs via a neural executor, allowing end-to-end training and gradient-based test-time adaptation that outperforms prior methods on combinatorial generalization tasks.
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Seeking the Unfamiliar but Memorable: Conceptual Creativity as Meta-Learning
Creativity is defined as meta-learning where a frozen diffusion creator optimizes candidates for rapid improvement by an adapting appraiser such as an autoencoder or CLIP adapter.
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A neurosymbolic Approach with Epistemic Deep Learning for Hierarchical Image Classification
A neurosymbolic model augments Swin Transformers with focal sets and fuzzy logic to produce calibrated hierarchical image classifications that respect logical constraints.
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Simultaneous Inference for Nonlinear Time Series, a Sieve M-regression Approach
Establishes a uniform Bahadur representation for sieve M-estimators under temporal dependence and constructs valid simultaneous confidence regions using Gaussian approximation and self-convolved bootstrap.