Active Prompting
Also called Active-Prompt.
Active prompting selects which questions to annotate with chain-of-thought exemplars by choosing those on which the model is most uncertain, measured by disagreement across sampled answers.
Description
Borrowing from active learning, it focuses human annotation effort on the examples most informative for the model, rather than on a fixed or random set.
Sources
- Diao et al. (2023). Active Prompting with Chain-of-Thought for Large Language Models.
Cite this entry
Protologue. (2026). Active Prompting. In Protologue: A Taxonomy of Prompting and LLM Techniques (v1.0.0, PTL-0023). https://protologue.com/t/active-prompting/
BibTeX
@misc{protologue_active_prompting,
title = {Active Prompting},
author = {{Protologue}},
year = {2026},
howpublished = {Protologue: A Taxonomy of Prompting and LLM Techniques, v1.0.0},
note = {Entry PTL-0023},
url = {https://protologue.com/t/active-prompting/}
}