Promptbreeder evolves both task prompts and the mutation prompts that improve them using LLMs, outperforming Chain-of-Thought and Plan-and-Solve on arithmetic and commonsense reasoning benchmarks.
arXiv preprint arXiv:2211.11260 , year=
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A bootstrap strategy for non-unitary CFTs uses statistical stability of OPE data across cross-ratios to optimize spectra, reproducing A-series minimal models and yielding candidate solutions for c>1.
Derives optimality constraints for nonnegative joint dictionary learning that explain observed SAE behaviors such as feature splitting, absorption, and dense antipodal features.
citing papers explorer
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Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution
Promptbreeder evolves both task prompts and the mutation prompts that improve them using LLMs, outperforming Chain-of-Thought and Plan-and-Solve on arithmetic and commonsense reasoning benchmarks.
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Bootstrapping non-unitary CFTs
A bootstrap strategy for non-unitary CFTs uses statistical stability of OPE data across cross-ratios to optimize spectra, reproducing A-series minimal models and yielding candidate solutions for c>1.
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How Optimality Structures Sparse Dictionaries: A Theory for Understanding SAE Representations
Derives optimality constraints for nonnegative joint dictionary learning that explain observed SAE behaviors such as feature splitting, absorption, and dense antipodal features.