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critique

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prompt-potter-optimizer

LLM-driven evolution of prompts and pipelines. Evolves the prompt and the pipeline's parameters together against your labeled data, cuts losing candidates early, and shows every measurement behind the winner. Open source.

  • Updated Oct 16, 2026
  • Python

Accepted to NeurIPS 2026 (Main Track). Reviewer precision and critique uptake are separable: a multi-agent protocol can detect errors well and still fail to repair them. Code, data and analysis for arXiv:2607.15388.

  • Updated Sep 25, 2026
  • Python

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