Summary of Apeer: Automatic Prompt Engineering Enhances Large Language Model Reranking, by Can Jin et al.
APEER: Automatic Prompt Engineering Enhances Large Language Model Reranking
by Can Jin, Hongwu Peng, Shiyu Zhao, Zhenting Wang, Wujiang Xu, Ligong Han, Jiahui Zhao, Kai Zhong, Sanguthevar Rajasekaran, Dimitris N. Metaxas
First submitted to arxiv on: 20 Jun 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The abstract presents a novel automatic prompt engineering algorithm called APEER, designed to optimize relevance ranking in Large Language Models (LLMs) for Information Retrieval (IR). Existing algorithms primarily focus on language modeling and classification tasks, leaving IR underexplored. APEER iteratively generates refined prompts through feedback and preference optimization, outperforming existing state-of-the-art manual prompts. The algorithm demonstrates substantial performance improvement with four LLMs and ten datasets, exhibiting better transferability across diverse tasks and models. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary APEER is a new way to help computers understand what we mean when we ask them questions or search for information. Right now, people have to tell the computer exactly how to ask its own question in order to get good results. But APEER makes it possible for computers to figure out how to ask better questions on their own. This can make searching and finding information much faster and easier. |
Keywords
» Artificial intelligence » Classification » Optimization » Prompt » Transferability
