| Fusion-in-Decoder (FiD) is a model described in the following paper: | |
| > Izacard, Gautier, and Édouard Grave. [Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering](https://aclanthology.org/2021.eacl-main.74/). _Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume_. 2021. | |
| We have replicated FiD training with our Wikipedia corpus variants and incorporated the model into our [PyGaggle](https://github.com/castorini/pygaggle) neural text ranking library. | |
| Our own efforts are described in the paper entitled: | |
| > Pre-Processing Matters! Improved Wikipedia Corpora for Open-Domain Question Answering. | |
| This is a FiD-large reader model for the wiki-text-6-3 corpus variant trained on the TriviaQA dataset. |