Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/tomekkorbak/measuring-non-trivial-compositionality
Code accompanying the paper Measuring non-trivial compositionality in emergent communication
https://github.com/tomekkorbak/measuring-non-trivial-compositionality
compositionality deep-learning emergent-communication generalization representation-learning
Last synced: about 2 months ago
JSON representation
Code accompanying the paper Measuring non-trivial compositionality in emergent communication
- Host: GitHub
- URL: https://github.com/tomekkorbak/measuring-non-trivial-compositionality
- Owner: tomekkorbak
- Created: 2020-07-21T15:18:39.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2021-12-18T14:51:14.000Z (about 3 years ago)
- Last Synced: 2024-10-10T20:18:13.848Z (2 months ago)
- Topics: compositionality, deep-learning, emergent-communication, generalization, representation-learning
- Language: Python
- Homepage: https://arxiv.org/abs/2010.15058
- Size: 118 KB
- Stars: 6
- Watchers: 2
- Forks: 3
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Measuring non-trivial compositionality
This repo contains the source code accompanying the paper [*Measuring non-trivial compositionality in emergent communication*](https://arxiv.org/abs/2010.15058) presented at NeurIPS 2020 workshop [Talking to Strangers: Zero-Shot Emergent Communication](https://sites.google.com/view/emecom2020).
All metrics and protocols implement a common API defined in `metrics.base.Metric` and `protocols.Protocol` and were designed to be reusable.
### Running
To install all the dependencies, run `pip install -r requirements.txt`. We assume Python 3.6+.
To reproduce the results and plots from the main experiment (how each metric scores each protocol), run `python experiment_1.py`.
To reproduce the results and plots from the experiment in appendix C (how the composition function in TRE affects compositionality scores), run `python experiment_2.py`.
To run init tests for the metrics, run `pytest`.
### Citing
```bibtex
@misc{korbak2020measuring,
title={Measuring non-trivial compositionality in emergent communication},
author={Tomasz Korbak and Julian Zubek and Joanna Rączaszek-Leonardi},
year={2020},
eprint={2010.15058},
archivePrefix={arXiv},
primaryClass={cs.NE}
}
```