EvoPrompt uses LLMs to run evolutionary operators on populations of prompts, outperforming human-engineered prompts by up to 25% on BIG-Bench Hard tasks across 31 datasets.
Large language models are human-level prompt engineers
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
years
2023 2roles
background 1polarities
background 1representative citing papers
GPT-4V processes interleaved image-text inputs generically and supports visual referring prompting for new human-AI interaction.
citing papers explorer
-
EvoPrompt: Connecting LLMs with Evolutionary Algorithms Yields Powerful Prompt Optimizers
EvoPrompt uses LLMs to run evolutionary operators on populations of prompts, outperforming human-engineered prompts by up to 25% on BIG-Bench Hard tasks across 31 datasets.
-
The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)
GPT-4V processes interleaved image-text inputs generically and supports visual referring prompting for new human-AI interaction.