Fermi Problems: A New Reasoning Challenge for AI

Fermi Problems are questions whose answer is a number that can only be reasonably estimated as a precise measurement of the value is either impossible or impractical.

This repository provides two datasets of such fermi problems along with annotations for the solution:

RealFP @ ./data/realFP. A collection of 928 fermi problems and their solutions expressed in the form a program.
SynthFP @ .data/synthFP. An auxilliary set of 10000 templated fermi questions, created by the authors.

Code for compiling the program in the dataset and computing the accuracy metric is provided in eval_utils.py. For more details on the datasets, please refer to our paper: How Much Coffee Was Consumed During EMNLP 2019? Fermi Problems: A New Reasoning Challenge for AI.

Inference

You can download a model finetuned on the realFP dataset here. Answers to your fermi questions can be obtained by executing the following command: python inference --question your_question_here. Make sure to check requirements.txt for any dependencies.

If you use the datasets or any other content shared in this repository, please cite our work:

@article{kalyan2021much,
  title={How Much Coffee Was Consumed During EMNLP 2019? Fermi Problems: A New Reasoning Challenge for AI},
  author={Kalyan, Ashwin and Kumar, Abhinav and Chandrasekaran, Arjun and Sabharwal, Ashish and Clark, Peter},
  journal={arXiv preprint arXiv:2110.14207},
  year={2021}
}