README.md

metadata

license: cc-by-4.0
task_categories:
  - question-answering
language:
  - en
size_categories:
  - 10K<n<100K

Literature Synthesis Queries

This dataset contains 50k real-world literature synthesis queries from our public demo.

Dataset Summary

This dataset contains real-world literature synthesis questions collected from users of a scientific question-answering system. Each entry includes:

• The user’s query (in natural language) (query)
• The subject of the question (e.g., computer science, medicine, engineering) (subject)
• The query intent (e.g., Literature Understanding, Paper Finding, Ideation, Other) (query intent)

The questions reflect realistic information needs from researchers and students, and often require retrieving, synthesizing, or summarizing scientific literature. The dataset is intended for research on retrieval-augmented generation, scientific question answering, and user intent classification.

License

This dataset is licensed under CC BY 4.0 . It is intended for research and educational use in accordance with Ai2's Responsible Use Guidelines.

Citation

@article{openscholar,
  title={{OpenScholar}: Synthesizing Scientific Literature with Retrieval-Augmented Language Models},
  author={Asai, Akari and He*, Jacqueline and Shao*, Rulin and Shi, Weijia and Singh, Amanpreet and Chang, Joseph Chee  and Lo,  Kyle and Soldaini, Luca and Feldman, Tian, Sergey and Mike, D’arcy and Wadden, David and Latzke, Matt and Sparks,Jenna and Hwang, Jena D. and Kishore, Varsha and Minyang and Ji, Pan and Liu, Shengyan and Tong, Hao and Wu, Bohao and Xiong, Yanyu and Zettlemoyer, Luke and Weld, Dan and Neubig, Graham and Downey, Doug and Yih, Wen-tau and Koh, Pang Wei and Hajishirzi, Hannaneh},
  journal={Arxiv},
  year={2024},
}