CALICO is presented, a human-centered, codebook-aligned annotation workflow that treats prompts as editable, versioned, and optimizable artifacts and integrates codebook parsing, prompt generation, result inspection, prompt versioning, natural language human feedback, and label-supervised prompt optimization through ex...
This work proves a PAC-Bayes bound guaranteeing that a dictionary extracted from successful trajectories has bounded expected description length on future successful behavior, and introduces ReuseRL, which grounds agentic RL in the Minimum Description Length (MDL) principle.
Zhikun Xu, Yu Feng, Jacob Dineen et al.· arXiv.org· 1 citation
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