LLM-URL: Large Language Models are Built-in Autoregressive Search Engines

Introduction & Setup

This repository contains the code for the paper Large Language Models are Built-in Autoregressive Search Engines(Accepted to ACL 2023).

• To get started, clone this repository and install the requirements:

git clone https://github.com/Ziems/llm-url
cd llm-url
pip install -r requirements.txt

• Rename .env.template to .env then add your openai api key

• Download the NQ and TriviaQA (tqa) datasets from Google drive: (we unified the formats) [link] then put these directories in the indatasets directory along with WebQ which is already there.

• Run retrieval (step1) on the dataset

python3 mainfunc.py
  --dataset {dataset}
  --task step1

• Run answer generation (step2):

python3 mainfunc.py
  --dataset {dataset}
  --task step2

Citation

@inproceedings{ziems-2023-large,
    title = "Large Language Models are Built-in Autoregressive Search Engines",
    author = "Ziems, Noah  and
      Yu, Wenhao  and
      Zhang, Zhihan  and
      Jiang, Meng",
    booktitle = "Findings of the Association for Computational Linguistics: ACL 2023",
    year = "2023"
}

Please feel free to cite our paper if you find this repository helpful in your research.