# LG AI Research — Can Large Language Models Improve Few-shot Retrieval for Complex Question Answering?

- Company: LG AI Research (lgresearch.ai)
- Announced: 2023-03-15
- Category: research-paper
- Coverage: not counted
- Announcement: yes
- Group: announcements
- Source: https://www.lgresearch.ai/blog/view?seq=314
- Record: https://forck.live/items/4903-can-large-language-models-improve-few-shot-retrieval-for-complex-question
- Subject: EXAONE

LG AI Research proposes PromptRank, a data-efficient retrieval method for multi-hop question answering that uses a large language model to rerank document paths based on the conditional likelihood of generating the question given the path.

## Evidence

Verbatim from https://www.lgresearch.ai/blog/view?seq=314:

> Enters our approach, dubbed PromptRank. ... PromptRank consists of two steps. First, a simple unsupervised retrieval method picks an initial set of document paths that have the potential to be relevant to the given question. Second, a more complex reranker model reweighs (or reranks) the paths obtained in the first step based on their relevance to the question.

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Record: https://forck.live/items/4903-can-large-language-models-improve-few-shot-retrieval-for-complex-question
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